2025-03-17T08:14:10Z https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/oai

oai:ojs.localhost:article/12953 2023-02-04T07:56:20Z Jurnal_Desain:ART

oai:ojs.localhost:article/6029 2021-07-30T16:54:43Z inference:ART

oai:ojs.localhost:article/10651 2022-02-21T13:10:48Z Faktor:ART

oai:ojs.localhost:article/23281 2024-08-03T08:15:42Z pkm:ART

oai:ojs.localhost:article/10200 2022-08-05T13:29:38Z Faktor:ART

oai:ojs.localhost:article/6795 2021-01-03T12:03:50Z Jurnal_Desain:ART

oai:ojs.localhost:article/6873 2021-12-08T14:08:08Z inference:ART

oai:ojs.localhost:article/11327 2022-08-10T13:15:15Z Faktor:ART

oai:ojs.localhost:article/23184 2024-09-30T06:07:04Z RDJE:ART

oai:ojs.localhost:article/11339 2022-02-03T20:51:33Z Deiksis:ART

oai:ojs.localhost:article/6977 2021-02-27T11:18:40Z diskursus:ART

oai:ojs.localhost:article/10413 2023-06-27T17:57:41Z STRING:ART

oai:ojs.localhost:article/5796 2021-04-06T13:01:13Z inference:ART

oai:ojs.localhost:article/11783 2022-10-01T00:11:07Z Deiksis:ART

oai:ojs.localhost:article/26650 2024-12-07T03:24:58Z RDJE:ART

oai:ojs.localhost:article/13177 2023-01-02T11:39:43Z sosio_ekons:ART

oai:ojs.localhost:article/6349 2021-02-19T11:26:35Z diskursus:ART

oai:ojs.localhost:article/16925 2023-08-22T11:41:09Z diskursus:ART

oai:ojs.localhost:article/6837 2021-04-06T13:01:13Z inference:ART

oai:ojs.localhost:article/7061 2021-04-12T13:48:34Z alursejarah:ART

oai:ojs.localhost:article/13774 2022-07-19T00:07:57Z RDJE:ART

oai:ojs.localhost:article/6030 2021-07-30T16:51:03Z inference:ART

oai:ojs.localhost:article/11224 2022-10-12T12:01:45Z Faktor:ART

oai:ojs.localhost:article/21007 2024-08-30T10:03:43Z JABE:ART

oai:ojs.localhost:article/10042 2021-07-06T12:04:19Z RDJE:ART

oai:ojs.localhost:article/5586 2021-04-20T14:50:24Z inference:ART

oai:ojs.localhost:article/9429 2021-08-10T19:36:01Z Faktor_Exacta:ART

Implementasi Metode K-Medoids Untuk Masalah Intrusion Detection System Menggunakan Bahasa Pemrograman Matlab Hutapea, Octaviani Talita, Aini Suri; Gunadarma University Based on data from the National Cyber And Crypto Agency (BSSN) of the Republic of Indonesia from 2018 to 2021, the threat of cyber attacks continues to experience a significant increase. In 2021, a significant change that is likely to be faced is with the emergence of new smart devices, which are more than just end-users and remotely connected networked devices. Surely, gives it the attention of all parties. There are many types of cyberattacks including Malware, Phishing, Ransomeware, etc. IDS (Intrusion Detection System) is a method that can detect suspicious activity in a system or network. Implementation of the Fuzzy K-Medoids method by using the Matlab programming language that retrieves data from KDDCUP’99 which has been normalized. The data used are normal data and anomaly attack data which are categorized as DoS, Probe, R2L, and U2R. From the research conducted the accuracy percentage is around 60-89% with three types of data preprocessing LPPM 2021-08-10 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9429 10.30998/faktorexacta.v14i2.9429 Faktor Exacta; Vol 14, No 2 (2021); 84-91 Faktor Exacta; Vol 14, No 2 (2021); 84-91 2502-339X 1979-276X 10.30998/faktorexacta.v14i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9429/4154 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/11312 2022-11-01T15:12:13Z Faktor_Exacta:ART

Auditing the Academic Information System of the Indonesian Christian University Toraja Using the Cobit 5 Framework Boas Gallaran, Ferayanti; Universitas Kristen Indonesia Toraja Pagiu, Chrismesi; Universitas Kristen Indonesia Toraja Palelleng, Srivan; Universitas Kristen Indonesia Toraja Rapid technological developments make all sectors vying to use the latest technology. No exception in the field of education, technology is a basic need to support the teaching and learning process. One example of the technology used by UKI Toraja is the UKI Toraja Ecampuz Academic Information System. This system has been in use since the end of 2018 until now. Since the use of the Ecampuz UKI Toraja Academic Information System, it has provided many benefits, especially for its users, namely lecturers, students and employees. However, a system is a man-made product, so nothing is perfect, neither is the academic system used by UKI Toraja. Based on this hypothesis, this study aims to audit the Ecampuz UKI Toraja Academic Information System using the COBIT 5 framework by focusing on the domains of Evaluating Governance, direction, monitoring (EDM), Align, Plan and Organize (APO), Build, Acquire, and Implement (BAI), Deliver, Service and Support (DSS), Monitor, Evaluate, Assess (MEA) so that the Academic Information System can support the progress of the University effectively and efficiently.The final result of this research is that the highest matrix value is 0.932 in APO7 and APO11, while the lowest matrix value is 0.546 at EDM4 and APO4. This means that in managing resources and quality at SIA UKI Toraja has been good but still lacking in optimizing resources and innovation at SIA UKI Toraja (Ecampuz) LPPM 2022-11-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11312 10.30998/faktorexacta.v15i3.11312 Faktor Exacta; Vol 15, No 3 (2022); 174-179 Faktor Exacta; Vol 15, No 3 (2022); 174-179 2502-339X 1979-276X 10.30998/faktorexacta.v15i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11312/5145 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/17296 2023-11-10T10:43:29Z Faktor_Exacta:ART

Penerapan Algoritma C4.5 dengan Optimasi Particle Swarm Optimization untuk Prediksi Kelulusan Mahasiswa Hermawati, Mercy; Universitas Indraprasta PGRI College is a place for students to pursue higher education. Both state and private universities compete to be the best universities to produce the best graduates. The number of student graduates is an indicator of the success of a higher education institution, which will have an impact on government accreditation and public assessment. The aim of this research is to predict student graduation in order to know whether they will graduate on time or late by applying data mining techniques, namely classification using the C4.5 algorithm to obtain patterns of student graduation delays and the particle swarm optimization (PSO) algorithm to increase the accuracy of the C4 algorithm. 5. Testing uses cross validation tests, confusion matrix and ROC curve. The results of this research are that the C4.5 algorithm with particle swarm optimization (PSO) has an accuracy value of 86.72%, which is better than the C4.5 algorithm, whose accuracy is 82.05% and the difference between them is 4.67%. The difference between the AUC value of 0.033 was obtained from the C4.5 algorithm model, which had an AUC value of 0.870 with a good classification diagnostic level, and the C4.5 algorithm with PSO had an AUC value of 0.903 with an excellent classification diagnostic level. IPS3 is the attribute that most influences the accuracy of student graduation. The results of the C4.5 algorithm rule with PSO can be applied to create applications for GUI-based student graduation predictions. LPPM 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17296 10.30998/faktorexacta.v16i3.17296 Faktor Exacta; Vol 16, No 3 (2023) Faktor Exacta; Vol 16, No 3 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17296/6119 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/21819 2024-07-17T04:29:56Z Faktor_Exacta:ART

Application of Ensemble Tree Algorithm for Installment Payment Arrears Prediction at Makmur Bersama Credit Union Khumaidi, Ali; Universitas Krisnadwipayana Darmawan, Risanto; Universitas Krisnadwipayana Reztrianti, Diajeng; UNKRIS One of the widely used machine learning techniques is the ensemble tree method, which is a combination of several classification trees where the final decision is based on the combined predictions of each tree. This approach produces better accuracy than a single classification tree. Two common methods used in the ensemble tree technique are boosting and bagging. This research will predict the status of installment payments at CU Makmur Bersama Credit Union. The method used is the bagging tree method, namely random forest and boosting, namely AdaBoost. To get optimal results, hyperparameter tuning is also carried out. The results showed that the boosting and bagging ensemble tree methods were able to handle the classification of cooperative loan installment payment status better than the distance approach, namely kNN (single classification). The performance of the boosting ensemble tree with the AdaBoost model has an accuracy of 72.89% better than the bagging ensemble tree with the random forest model whose accuracy is 72.08%. LPPM 2024-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21819 10.30998/faktorexacta.v17i2.21819 Faktor Exacta; Vol 17, No 2 (2024); 161-166 Faktor Exacta; Vol 17, No 2 (2024); 161-166 2502-339X 1979-276X 10.30998/faktorexacta.v17i2 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21819/6797 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/12039 2022-08-10T14:47:36Z Faktor_Exacta:ART

Pengujian IaC Berbasis DevOps dan Ansible Menggunakan Metode Black Box Testing Pratama, I Putu Agus Eka; Udayana University Putra, Putu Bayu Suarnata Wahyu; Udayana University The development of information technology, which is followed by an increase in the need for devices and computing resources for services on computer networks, requires cost and time for the configuration and development process. Infrastructure as Code (IaC) based on DevOps using Ansible, is a solution to this problem, by combining development and operational processes. However, post-implementation, it is necessary to test on the application side to determine the functionality of the running system. For this reason, in this research, a Black Box Testing method with three steps is proposed for testing the implementation of DevOps-based IaC using Ansible. The test results show that the implementation of Ansible for DevOps-based IaC was successfully carried out by configuring the host node and running the Ansible playbook from the host server. LPPM 2022-08-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/12039 10.30998/faktorexacta.v15i2.12039 Faktor Exacta; Vol 15, No 2 (2022) Faktor Exacta; Vol 15, No 2 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i2 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/12039/4914 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/12039/2223 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/17343 2023-07-31T11:47:36Z Faktor_Exacta:ART

APPLICATION OF SOCIAL MEDIA PLATFORM TECHNOLOGY IN PUBLICITY STRATEGY PROSUMPTION OF DIGITAL WORKERS IN THE MARKETPLACE Wulan, Rayung Rusadi, Udi; Institut Ilmu Sosial dan Politik (IISIP), Jakarta The existence of social media platforms in the post-covid-19 pandemic era has increased sharply and penetrated various sectors among workers, especially digital workers. Various efforts to apply social media platform technology continue to increase in efforts to publicity strategies for the production of digital workers. platformsSocial media as a form of publicity expression for the production of digital workers has spread to various devices with the help of social media platforms with various applications. Social media platform technology as an effort to improve digital worker production publicity strategies that can increase the current marketplace rating. The purpose of this study is to apply social media platform technology which can be a strategy in publicity for digital workers in the marketplace. The method used in this study with the approachcomparative causal quantitative using surveys from several digital consumers who often use various marketplaces in their daily lives. , by adopting the slovin theory. In the testing phase of 368 respondents, there is a truth hypothesis from 105 digital consumers who are eligible for further testing in the marketplace with a simple linear regression analysis. Generated based on calculations with slovin theoryThe Publicity Strategy for Producing Digital Workers in the dominant Marketplace using the Social Media Platform shows a result of 95.2%, this result shows how high the presentation of these results is. LPPM 2023-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17343 10.30998/faktorexacta.v16i2.17343 Faktor Exacta; Vol 16, No 2 (2023) Faktor Exacta; Vol 16, No 2 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17343/5830 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/17343/3443 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/22393 2024-05-03T08:19:40Z Faktor_Exacta:ART

Eksplorasi Teknik Web Scraping pada Data Mining: Pendekatan Pencarian Data Berbasis Python Chrisinta, Debora; Program Studi Teknologi Informasi, Universitas Timor, Indonesia Simarmata, Justin Eduardo; Program Studi Pendidikan Matematika, Universitas Timor, Indonesia Web scraping was an automated information extraction technique from web pages for data collection and was applied in data mining. Two common algorithms used in data mining are clustering and classification. The data source used originated from the Google Search Engine. The design of the web scraping script using Python was implemented to collect data, process HTML, and extract information from web pages. Data was successfully gathered from the Google Search Engine regarding tourism, with the number of links and processing time measured. Data processing involved cleaning the data and implementing hierarchical clustering algorithms. The evaluation was carried out by selecting the optimal number of clusters using the Dunn index. Subsequently, the data was used to train a decision tree model, and the results were evaluated using accuracy, confusion matrix, and classification reports. The results of this research indicated that the importance of web scraping in data mining could provide a comprehensive understanding of the effectiveness of web scraping techniques and the application of data mining. LPPM 2024-05-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/22393 10.30998/faktorexacta.v17i1.22393 Faktor Exacta; Vol 17, No 1 (2024) Faktor Exacta; Vol 17, No 1 (2024) 2502-339X 1979-276X 10.30998/faktorexacta.v17i1 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/22393/6608 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/7652 2021-04-27T14:57:10Z Faktor_Exacta:ART

PERANCANGAN MACHINE VISION UNTUK PEMILAH KUALITAS PRODUK AIR MINUM DALAM BOTOL 600ML DI WTP PUTOI PNJ Alam, Nur; Politeknik Negeri Jakarta Figana, Dian Penelitian ini telah berhasil melakukan perancangan alat untuk memilah kualitas air minum dalam kemasan botol 600ml di WTP PNJ. Air minum yang sangat dibutuhkan oleh tubuh manusia adalah air minum yang bersih, sehat dan higienis. Saat ini mayoritas air minum yang ada khususnya di wilayah Jakarta adalah air minum dalam kemasan. Air sumur yang ada saat ini mayoritas telah tercemar oleh bakteri maupun unsur lain dari berbagai sumber antara lain; dari limbah pabrik, pom bensin, maupun berasal dari limbah rumah tangga lainnya. Politeknik Negeri Jakarta sebagai Perguruan Tinggi Negeri yang saat ini sedang menuju visi unggul berkelas dunia, telah mempersiapkan beberapa fasilitas pembelajaran yang bertujuan untuk meningkatkan kompetensi dosen dan mahasiswa dalam mengembangkan keunggulannya. Salah satu keunggulan tersebut yaitu adanya Pusat Unggulan Teknologi Otomasi Industri (PUTOI). Keunggulan di PUTOI saat ini yang dikembangkan adalah pusat teknologi dan riset mengenai bidang teknologi otomasi industri. PUTOI telah memiliki sistem teknologi otomasi yang canggih yaitu dalam bidang teknologi otomasi Water Treatment Plant (WTP). Dengan demikian sebelum beredar dalam bentuk air minum maka dibutuhkan lagi sebuah alat otomasi untuk memeriksa kualitas dari produk air minum tersebut. Saat ini dibutuhkan sebuah mesin untuk bekerja sebagai Quality Control dari produk air minum WTP PNJ. Peneliti telah berhasil membuat sebuah rancangan mesin pemilah kualitas produk air minum dari WTP PNJ berbasis Machine Vision. Mesin vision ini merupakan metode baru yang sangat diperlukan dalam penentuan kualitas suatu produk secara otomatis. Dimana mesin vision ini dapat memilah kualitas suatu produk air minum berdasarkan level air, kualitas kemasan, kejernihan air, maupun kualitas segel dan barcodenya. LPPM 2021-03-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7652 10.30998/faktorexacta.v14i1.7652 Faktor Exacta; Vol 14, No 1 (2021); 1-8 Faktor Exacta; Vol 14, No 1 (2021); 1-8 2502-339X 1979-276X 10.30998/faktorexacta.v14i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7652/3942 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/9447 2022-01-26T13:47:30Z Faktor_Exacta:ART

Prediksi Penjualan Kendaraan Niaga Berdasarkan Kinerja Purnajual dan Pertumbuhan Pasar Ginanto, Novika Wirawan, Setia; Universitas Gunadarma Indonesia is one of the largest automotive market in South East Asia with highly demand of passenger and commercial vehicle. Commercial vehicle is used to distribute product to customers, then commercial vehicle strongly related with business growth. Gaikindo said that automotive business growth went down as 10.6%, it would effect to automotive company performance, especially vehicle stock ratio. Vehicle stock ratio can affect to financial and resources planning. Therefore, the forecasting was to be important to predict the market demand in future. Basically, commercial vehicle would be used in along day due to business value, therefore aftersales services was critical point. In this case, sales forecasting of commercial vehicle (dependent variable) was approached by trend of aftersales performance and market growth (independent variable). Aftersales performance consist of aftersales revenue and unit served volume, then market growth using SAMSAT data. Prediction method used multiple linear regression due to forecasting capability with many variables. And the result using SPSS application was confirmed that independent variable affect to commercial vehicle sales volume and not multicollinearity. The result error of MAD was 3.80. So that, sales forecasting of commercial vehicle can be predicted based on aftersales performance and market growth using multiple linear regression. Indonesia is one of the largest automotive market in South East Asia with highly demand of passenger and commercial vehicle. Commercial vehicle is used to distribute product to customers, then commercial vehicle strongly related with business growth. Gaikindo said that automotive business growth went down as 10.6%, it would effect to automotive company performance, especially vehicle stock ratio. Vehicle stock ratio can affect to financial and resources planning. Therefore, the forecasting was to be important to predict the market demand in future. Basically, commercial vehicle would be used in along day due to business value, therefore aftersales services was critical point. In this case, sales forecasting of commercial vehicle (dependent variable) was approached by trend of aftersales performance and market growth (independent variable). Aftersales performance consist of aftersales revenue and unit served volume, then market growth using SAMSAT data. Prediction method used multiple linear regression due to forecasting capability with many variables. And the result using SPSS application was confirmed that independent variable affect to commercial vehicle sales volume and not multicollinearity. The result error of MAD was 3.80. So that, sales forecasting of commercial vehicle can be predicted based on aftersales performance and market growth using multiple linear regression. LPPM 2022-01-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9447 10.30998/faktorexacta.v14i4.9447 Faktor Exacta; Vol 14, No 4 (2021); 214-224 Faktor Exacta; Vol 14, No 4 (2021); 214-224 2502-339X 1979-276X 10.30998/faktorexacta.v14i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9447/4504 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/13554 2023-03-25T15:10:10Z Faktor_Exacta:ART

Optimalisasi Keuntungan Produk Furniture Menggunakan Metode Simpleks dan Software POM-QM Berbasis Website Sitio, Sartika Lina Mulani; Universitas Pamulang Zakaria, Hadi; Universitas Pamulang Today, many people are competing to build a business to meet their basic needs. We know that the development of SMEs will have a significant impact on the pace of the Indonesian economy. MJ Furniture is one of the stores that runs a furniture retail business. One of the problems that MJ furniture stores often face is determining production to get the maximum benefit they need to get from their daily production activities. This study aims to solve the problems encountered in the MJ furniture business by making linear programming more effective and efficient. The method used to collect the data is in the form of observations and interviews with MJ furniture stores. Meanwhile, the data analysis was performed using the simplex method and POM-QM software. Using Simplex calculation results and the POM-QM application, the MJ shop makes a profit of IDR 5,743,000 by producing 30 mattresses, 10 tables and 13 wardrobes per day. The system is implemented using the web programming language, PHP, and data management is performed using MySQL. LPPM 2023-03-23 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13554 10.30998/faktorexacta.v16i1.13554 Faktor Exacta; Vol 16, No 1 (2023) Faktor Exacta; Vol 16, No 1 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13554/5521 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/21040 2024-01-09T11:00:57Z Faktor_Exacta:ART

Implementasi Metode Perbandingan Eksponensial Dalam Sistem Pendukung Keputusan Pemberian Kredit Nasabah Pada PT Bank DKI Cabang Syariah Wahid Hasyim Fajriah, Riri; Magister Ilmu Komputer Fakultas Teknologi Informasi Universitas Budi Luhur Melyana, Melyana; Magister Ilmu Komputer Fakultas Teknologi Informasi Universitas Budi Luhur Triyono, Gandung; Program Studi Sistem Informasi Fakultas Teknologi Informasi Universitas Budi Luhur PT Bank DKI Cabang Syariah Wahid Hasyim adalah cabang usaha yang melayani segmentasi pasar syariah dari PT Bank DKI sebagai BUMD dari Pemerintah Provinsi DKI Jakarta. Adapun produk bank yang ditawarkan terkait jenis layanan keuangan dan berbagai jenis kredit yang ditawarkan kepada calon debitur, seperti Kredit Pemilikan Rumah (KPR), Mikro UMKM, Kredit Multiguna, Bank Garansi. Permasalahan yang dihadapi saat ini adalah masih cukup signifikan kasus kredit macet di bank akibat kesalahan keputusan dalam pemberian kredit dari data analisa kelayakan calon debitur. Oleh karena itu, tujuan penelitian ini adalah untuk merancang sistem pendukung keputusan dengan menggunakan metode waterfall analysis dengan model perbandingan eksponensial dimana sistem ini akan digunakan oleh Relationship Manager (RM) untuk mengevaluasi kelayakan kredit calon debitur dengan lebih tepat dan akurat. Hasil penelitian ini menyajikan rancangan sistem pendukung keputusan dengan metode perbandingan eksponensial yang dapat membantu proses analisa kredit dari data-data calon debitur yang diproses untuk menghasilkan ranking penilaian kelayakan pemberian kredit, dimana keputusan pemberian kredit diambil berdasarkan nilai tertinggi hasil perhitungan MPE dan hasil ini akan menjadai landasan bagi Relationship Manager sebagai prioritas calon debitur untuk proses selanjutnya mendapatkan persetujuan kredit dari Pemimpin Cabang sebagai penyelia kredit di PT Bank DKI Cabang Syariah Wahid Hasyim. LPPM Universitas Budi Luhur 2024-01-08 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21040 10.30998/faktorexacta.v16i4.21040 Faktor Exacta; Vol 16, No 4 (2023) Faktor Exacta; Vol 16, No 4 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21040/6292 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/21040/4367 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/7071 2020-12-17T16:06:32Z Faktor_Exacta:ART

Pengaruh Electronic Word of Mouth terhadap Keputusan Pembelian Tiket Kereta api Daring Prastuti, Dewi Indah Karyanti, Yuli Penelitian ini tentang analisis pengaruh elerctronic word of mouth (e-WOM) dengan variabel intensitas (X1), konten (X2), pendapat positif (X3), pendapat negatif (X4) terhadap keputusan pembelian tiket kereta api daring. Penelitian bertujuan untuk : (1) mengetahui pengaruh secara parsial intensitas terhadap keputusan pembelian tiket kereta api daring; (2) mengetahui pengaruh secara parsial konten terhadap keputusan pembelian tiket kereta api daring; (3) mengetahui pengaruh secara parsial pendapat positif terhadap keputusan pembelian tiket kereta api daring; (4) mengetahui pengaruh secara parsial pendapat negatif terhadap keputusan pembelian tiket kereta api daring; (5) mengetahui pengaruh secara simultan intensitas, konten, pendapat positif dan pendapat negatif terhadap keputusan pembelian tiket kereta api daring. Penelitian menggunakan metode penelitian kuantitatif dengan teknik sampel simple random sampling. Teknik pengumpulan data dengan kuesioner yang dibagikan daring melalui media sosial kepada konsumen transportasi kereta api wilayah kereta Pulau Jawa dibulan Januari 2019 – September 2019 yang pernah membeli tiket kereta api daring sebanyak 400 sampel. Analisis data dengan regresi linear berganda, yaitu uji t dan uji F. Hasil penelitian menunjukkan : (1) secara parsial intensitas tidak berpengaruh terhadap keputusan pembelian tiket kereta api daring dibuktikan dengan nilai thitung -0,984 < nilai ttabel 1,965 dan nilai Sig. 0,326 > 0,05; (2) secara parsial konten berpengaruh terhadap keputusan pembelian tiket kereta api daring dibuktikan dengan nilai thitung 5,703 > nilai ttabel 1,965 dan nilai Sig. 0,000 < 0,05; (3) secara parsial pendapat positif berpengaruh terhadap keputusan pembelian tiket kereta api daring dibuktikan dengan nilai thitung 4,893 > nilai ttabel 1,965 dan nilai Sig. 0,000 < 0,05; (4) secara parsial pendapat negatif tidak berpengaruh terhadap keputusan pembelian tiket kereta api daring dibuktikan dengan nilai thitung 1,810 < nilai ttabel 1,965 dan nilai Sig. 0,071 > 0,05; (5) secara simultan intensitas, konten, pendapat positif dan pendapat negatif berpengaruh terhadap keputusan pembelian tiket kereta api daring dibuktikan dengan nilai Fhitung 23,784 > Ftabel 2,394 dan nilai Sig. 0,000 < 0,05. LPPM 2020-11-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7071 10.30998/faktorexacta.v13i3.7071 Faktor Exacta; Vol 13, No 3 (2020) Faktor Exacta; Vol 13, No 3 (2020) 2502-339X 1979-276X 10.30998/faktorexacta.v13i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7071/3537 Copyright (c) 2020 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/23936 2024-10-30T05:13:35Z Faktor_Exacta:ART

Penentuan mahasiswa berprestasi menggunakan algoritma FP-Growth dan SAW Ridwan, Wawan; Universitas Mercu Buana Gunawan, Wawan; Universitas Mercu Buana This research discusses the importance of utilizing technology in inventory management and student achievement determination. The transformation from manual systems to computerized systems has proven to increase efficiency and accuracy. In determining outstanding students, the criteria used often focus solely on academic aspects, neglecting other skills such as leadership and creativity. This study proposes the use of the FP-Growth and Simple Additive Weighting (SAW) algorithms to address this issue. FP-Growth is used to identify high-frequency patterns in student achievement data, while SAW assigns weights to each criterion variable for more accurate decision-making. The criteria for assessment include GPA, student achievements, study duration, and activity participation. The implementation is expected to provide a more effective solution in determining outstanding students and managing inventory. The FP-Growth method helps identify significant patterns in transaction data, while SAW assists in ranking alternatives based on specified criteria. This research demonstrates that the combination of these two algorithms can improve accuracy and efficiency in inventory management and student achievement determination, providing a competitive advantage for institutions. Based on the research results, the ranking of outstanding students is led by student C, followed by student B, with respective scores of 0.8875 and 0.825. LPPM 2024-10-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/23936 10.30998/faktorexacta.v17i3.23936 Faktor Exacta; Vol 17, No 3 (2024); 306-313 Faktor Exacta; Vol 17, No 3 (2024); 306-313 2502-339X 1979-276X 10.30998/faktorexacta.v17i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/23936/7106 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/9365 2021-12-24T14:22:10Z Faktor_Exacta:ART

ALGORITMA NEURAL NETWORK BACKPROPAGATION UNTUK PREDIKSI HARGA SAHAM PADA TIGA GOLONGAN PERUSAHAAN BERDASARKAN KAPITALISASINYA Santi, Nopri Widodo, Suryarini; Universitas Gunadarma Stock is one type of investment where investors can gain profits in the form of capital gains and dividends. Types of shares based on the level of capitalization are divided into 3 types, namely the first layer (blue chips), the second layer, and the third layer. One of the techniques that investors use in order to make a profit is technical analysis, which is using data of past stock prices and volumes based on the assumption that trends can recur following historical data patterns. Based on the assumptions of technical analysis, it is possible to use data mining to predict stock prices. In this study, stock price predictions will be carried out by comparing three types of companies based on their capitalization, for first layer stocks using PT. Bank Central Asia Tbk (BBCA), the second layer using PT. XL Axiata Tbk (EXCL), and third layer using PT Pembangunan Graha Lestari Indah Tbk. The data mining algorithm that will be used is the Neural Network Backpropagation method. The attributes used as predictors are open, high, low, and volume, while the objective attribute is close. This study aims to determine whether daily stock historical data can be used to predict stock prices using the Neural Network Backpropagation method and how to compare the results of predictions between 3 companies with different capitalization levels. The result of RMSE for BBCA by using the most optimal combination of parameters and 3 hidden layer is 123.84. The result of RMSE for EXCL by using the most optimal combination of parameters and hidden layer 2 is 37.36. The result of RMSE for PGLI by using the most optimal combination of parameters and hidden layer 6 is 6.16. So that the backpropagation neural network algorithm is most optimally applied to third layer companies, PT. Pembangunan Graha Lestari Indah Tbk because the RMSE value is the smallest. LPPM 2021-10-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9365 10.30998/faktorexacta.v14i3.9365 Faktor Exacta; Vol 14, No 3 (2021); 131-139 Faktor Exacta; Vol 14, No 3 (2021); 131-139 2502-339X 1979-276X 10.30998/faktorexacta.v14i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9365/4320 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/14578 2023-01-24T12:06:17Z Faktor_Exacta:ART

Penentuan Batas Gain Kanal Modulasi Adaptif V2V dengan Doppler Shift yang Bervariasi Menggunakan Machine Learning Kurniawati, Nazmia; Politeknik Negeri Jakarta Novfitri, Aisyah; Institut Teknologi Telkom Jakarta Tyas, Arti Suryaning; Politeknik Negeri Jakarta Doppler shift is a phenomenon that occurs when the vehicle is moving. The effect of Doppler shift is a degradation in performance of Vehicle to Vehicle (V2V) communication. Adaptive modulation is a technique to improve the performance. It is done by adjusting the modulation scheme used according to noise conditions while keeping the Bit Error Rate (BER) value not exceeding 10-3. In this research, three Doppler shift values are used. The shift is derived from speed limit determined by The Government of Indonesia. Then machine learning algorithm is used to predict channel gain threshold that can optimize the use of Signal to Noise Ratio (SNR) with a BER limit of 10-3. From the prediction results, it is found that by implementing the predicted channel gain threshold, the SNR required by adaptive modulation has the lowest value compared to non-adaptive modulation schemes. The lower the required SNR value, the communication is more resistant to noise interference. LPPM 2023-01-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14578 10.30998/faktorexacta.v15i4.14578 Faktor Exacta; Vol 15, No 4 (2022); 213-222 Faktor Exacta; Vol 15, No 4 (2022); 213-222 2502-339X 1979-276X 10.30998/faktorexacta.v15i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14578/5349 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/19415 2023-11-10T10:41:57Z Faktor_Exacta:ART

Kerangka Kerja Evaluasi dalam Menentukan Kendaraan Kargo yang Optimal Menggunakan Analytic Hierarchy Process Setiawan, Santoso; Universitas Nusa Mandiri Sulistyowati, Daning Nur; Universitas Nusa Mandiri This research aims to develop an evaluation framework in determining the optimal cargo vehicle (freight transportation) using the Analytic Hierarchy Process (AHP) method. The selection of the right cargo vehicle is crucial in logistics management to ensure the efficiency and sustainability of business operations. This research, combines the AHP approach with multi-criteria evaluation to help make better decisions. The proposed evaluation framework consists of several steps, namely: determining relevant criteria in cargo vehicle selection, including factors such as reliability, fuel efficiency, and vehicle price. Then collecting data related to these criteria from reliable sources. Next, conduct a pairwise comparison analysis with AHP to obtain the relative weight of each criterion. And finally calculate the relative performance value for each cargo vehicle based on the set criteria. In this study, the authors applied the proposed evaluation framework to a logistics operation case study. The results show that the use of the AHP method in cargo vehicle selection can help make more systematic and objective decisions. This evaluation framework also allows stakeholders to identify the cargo vehicle that best suits their needs. LPPM 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19415 10.30998/faktorexacta.v16i3.19415 Faktor Exacta; Vol 16, No 3 (2023) Faktor Exacta; Vol 16, No 3 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19415/6114 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/23824 2024-10-30T05:13:35Z Faktor_Exacta:ART

Pemanfaatan Perpustakaan Digital (E-Library) Sebagai Salah Satu Strategi Peningkatan Kualitas Pendidikan dan Penelitian di Perguruan Tinggi Himawan, Himawan; Sekolah Tinggi Teknologi Informasi NIIT Kusuma Wardani, Deyana; Politeknik Astra Kartika Kusuma Winahyu, Raden Rara; Politeknik Astra The university plays an important role in educating the future generations of the country. One of the universities efforts is to use the facilities and infrastructure in their respective universities to achieve this goal. Astra Polytechnic is one of the higher education institutions in the Cikarang region with unsuitable infrastructure to improve the quality of university services and research activities for all academic communities at the Astra Polytechnic Campus. The infrastructure is the campus library that is still operated in traditional ways, which certainly does not meet the information needs of the digitalization era, which requires the management and delivery of up-to-date and accurate information. Consequently, the Astra University Research and Community Service Institute (LP2M) and the Information Management Study Programme collaborated to establish digital libraries to improve the quality of university services for the entire Astra University College community. In addition, libraries must change (transformation) in order to survive today's digitalization. Ultimately, the use of library information systems is expected to help librarians and library staff manage library collections, memberships and all transactions, so that librarians have more time to do other things and be more efficient in terms of time management. LPPM 2024-09-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/23824 10.30998/faktorexacta.v17i3.23824 Faktor Exacta; Vol 17, No 3 (2024); 212-220 Faktor Exacta; Vol 17, No 3 (2024); 212-220 2502-339X 1979-276X 10.30998/faktorexacta.v17i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/23824/7097 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/13211 2022-08-12T10:33:38Z Faktor_Exacta:ART

Model Machine Learning Klasifikasi Data Sekolah TK Berdasarkan Status dan Kabupaten rahman, abdu; Universitas Indraprasta PGRI Ismawan, Fiqih Klasifikasi status sekolah menjadi parameter khusus bagi beberapa kalangan orang tua dalam melakukan pemilihan sekolah untuk anak yang dinginkan, beberapa pertimbangan khusus dalam penentuan sekolah salah satunya adalah status sekolah, jumlah sekolah, jumlah guru, jumlah murid dan jumlah ruang kelas. Makalah ini melaporkan bahwa data status sekolah TK kabupaten dan kota administrasi provinsi DKI Jakarta dapat dilakukan klasifikasi berdasarkan cluster dan domain data, dengan mempartisi data ke dalam cluster sehingga data yang memiliki karakteristik yang sama dikelompokkan ke dalam satu cluster yang sama dan data yang mempunyai karateristik yang berbeda dikelompokan ke dalam cluster yang lain. Metode klasifikasi yang digunakan adalah Levenshtein Distance dan K-Means Clustering, sumber data yang digunakan dalam penelitian ini adalah data sekunder yang diperoleh data.jakarta.go.id. Data sekunder yang digunakan adalah data sekolah dari 12 record kabupaten dan kota di Jakarta. Penelitian ini bertujuan untuk membuat model dan menentukan kriteria serta menganalisis akurasi klasifikasi antara ketiga metode tersebut dalam klasifikasi Data Sekolah TK Berdasarkan Status dan Kabupaten/Kota Administrasi Provinsi DKI Jakarta. Setelah dilakukan pengujian maka hasil Silhouette Score berdasarkan Average dari 4 atribut yaitu Cluster C1 dari score 0,691355 sampai 0,718406, Cluster C2 dari score 0,745171 sampai 0,747778 dan Cluster C3 dari score 0,601115 sampai 0,647377. Hasil Penelitian ini berupa pemodelan data dengan menggunakan parameter yang diambil dari data.jakarta.go.id kemudian diuji menggunakan beberapa model klasifikasi yang terdapat pada Machine Learning. LPPM Universitas Indraprasta PGRI 2022-08-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13211 10.30998/faktorexacta.v15i2.13211 Faktor Exacta; Vol 15, No 2 (2022) Faktor Exacta; Vol 15, No 2 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13211/4928 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/16657 2023-07-31T11:38:35Z Faktor_Exacta:ART

Implementasi Metode Support Vector Machine Dengan Algoritma Genetika Pada Prediksi Konsumsi Energi Untuk Gedung Beton Bertulang Syaputra, Asep; Institut Teknologi Pagar Alam Muslim, Buhori; Universitas Putra Indonesia (UNPI) Cianjur Prawira, Nanda S.; Institut Teknologi Pagar Alam edowinsyah, Edowinsyah; Institut Teknologi Pagar Alam Informasi tentang konsumsi energi sangat penting dalam mengukur efisiensi energi dan penghematan energi dalam bangunan. Konsumsi energi ini mengacu pada jumlah energi yang dibutuhkan untuk memberi daya pada bangunan pada waktu tertentu. Dengan mengetahui informasi ini, kita dapat mengevaluasi konsumsi energi yang ada dan membuat perubahan yang diperlukan untuk mengurangi penggunaan energi yang tidak perlu. Dalam jangka panjang, penghematan energi dapat membantu mengurangi biaya dan juga memberikan manfaat bagi lingkungan dengan mengurangi emisi gas rumah kaca yang dihasilkan oleh bangunan. Oleh karena itu, memperoleh informasi konsumsi energi yang akurat sangat penting bagi semua pihak yang terlibat dalam perencanaan, pembangunan, dan pengelolaan bangunan. Selama beberapa dekade terakhir, konsumsi energi di bangunan terus meningkat di seluruh dunia, dan sebagian besar konsumsi energi ini berasal dari Pemanasan, Ventilasi, dan Penyejuk Udara (HVAC) di dalam bangunan. Untuk mengatasi masalah ini, penelitian dilakukan dengan membuat model mesin vektor dukungan yang menggunakan algoritma genetika untuk memprediksi konsumsi energi di bangunan secara akurat. Dalam penelitian ini, dua model mesin vektor dukungan diuji, yaitu support vector machine dan support vector machine yang menggunakan algoritma genetika. Hasil pengujian menunjukkan bahwa model support vector machine memberikan nilai RMSE sebesar 2,6. Selanjutnya, algoritma genetika digunakan untuk mengoptimalkan parameter C dan memilih variabel prediktor yang paling relevan, dan hasilnya adalah nilai RMSE sebesar 1,7 dan hanya 3 variabel prediktor yang dipilih. Pada tahap selanjutnya, optimasi parameter dan pemilihan fungsi dilakukan untuk mencapai nilai RMSE terendah yang mungkin, dan hasilnya adalah RMSE sebesar 1,537. Dengan demikian, algoritma mesin vektor dukungan yang menggunakan algoritma genetika dapat memberikan solusi yang akurat dan efektif dalam memprediksi konsumsi energi di bangunan dengan nilai kesalahan terkecil. LPPM 2023-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16657 10.30998/faktorexacta.v16i2.16657 Faktor Exacta; Vol 16, No 2 (2023) Faktor Exacta; Vol 16, No 2 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16657/5828 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16657/5829 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/20473 2024-07-17T04:29:56Z Faktor_Exacta:ART

PENERAPAN ALGORITME BACKPROPAGATION NEURAL NETWORK UNTUK ESTIMASI JUMLAH KASUS DBD BERDASARKAN DATA CUACA Raissa, Benita Hasna Rusdah, Rusdah Dengue fever is widespread throughout the tropics which tends to have a seasonal pattern, namely before and after the rainy season. Infection is caused by one of the closely related dengue viruses, commonly called a serotype, which causes mild symptoms to symptoms that require medical treatment and hospitalization, even death can occur if the case is severe. Based on surveillance data, the number of cases in 2022 will be 3,190 people. One of the efforts to reduce the incidence of DHF is by forecasting the incidence of DHF to prevent an increase in DHF cases which continues every year. This research was forecasted using the independent variables average temperature, average humidity, average rainfall, and wind speed. The data used is public through surveillance and the BMKG website and the data used is data from 2018 to 2022. In this study using the backpropagation neural network algorithm, the model used is 4-3-1, where there are 4 variables in the input layer, 3 units in the hidden layer, 1 unit in the output layer with a learning rate value of 0.04, and momentum of 0.09 and the results are RMSE 4,347. LPPM 2024-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/20473 10.30998/faktorexacta.v17i2.20473 Faktor Exacta; Vol 17, No 2 (2024); 118-130 Faktor Exacta; Vol 17, No 2 (2024); 118-130 2502-339X 1979-276X 10.30998/faktorexacta.v17i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/20473/6793 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/9057 2021-04-27T14:57:10Z Faktor_Exacta:ART

Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi Menggunakan Metode Profile Matching APRIYANI, DWI DANI The calculation of scores that are still comprehensive for each student results in assessments that tend to be less objective. This has an impact on the selection of outstanding students which is less accurate and tends to be non-objective. This requires a decision support system for outstanding students. A decision support system using the profile matching method is one of the most frequently used methods because it can match criteria and has an accurate final decision. The weight criteria used are knowledge and skills, while the criteria for assessing outstanding students are report cards, learning attitudes, extracurricular activities, discipline, and attendance. With the existence of a decision support system for outstanding students, it is hoped that it can help teachers to be more objective in determining student achievement decisions. LPPM 2021-03-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9057 10.30998/faktorexacta.v14i1.9057 Faktor Exacta; Vol 14, No 1 (2021); 44-54 Faktor Exacta; Vol 14, No 1 (2021); 44-54 2502-339X 1979-276X 10.30998/faktorexacta.v14i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9057/3947 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/25201 2025-02-25T08:18:00Z Faktor_Exacta:ART

Analisis Model Matematika dan Simulasi Penyebaran dan Penanganan Penyalahgunaan Narkoba di Indonesia Ristiawan, Rifki; Universitas Indraprasta PGRI Endaryono, Endaryono; Universitas Indraprasta PGRI Mahyudi, Mahyudi; Universitas Indraprasta PGRI he increasing abuse of narcotics, psychotropic substances and addictive substances is a big problem in Indonesia today. The spread of drugs is increasing rapidly to the point that it can be considered a disaster. This research uses literature study methods and data analysis to determine assumptions and distribution models, then analyzes the models and carries out numerical simulations. A mathematical model was created to see the pattern of the spread of drug abuse and analyzed analytically to determine the existence of an equilibrium point and the type of stability, as well as to obtain the basic reproduction number . Numerical simulations were carried out to see distribution patterns in the next few years. From the results of the numerical simulations, information was obtained that to suppress the spread of drug abuse, efforts that can be made are to reduce the rate of recruitment of vulnerable classes by dealers and the rate of change from users to dealers. LPPM 2025-02-11 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/25201 10.30998/faktorexacta.v17i4.25201 Faktor Exacta; Vol 17, No 4 (2024); 357-365 Faktor Exacta; Vol 17, No 4 (2024); 357-365 2502-339X 1979-276X 10.30998/faktorexacta.v17i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/25201/7388 Copyright (c) 2025 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/11421 2022-07-14T12:04:56Z Faktor_Exacta:ART

Preferensi Masyarakat Terhadap Quick Response Code Indonesian Standard Sebagai Sarana Teknologi Pembayaran Digital Mayanti, Rina The development of electronic money transactions have grown rapidly especially in the digital payment sector. This study aims to analyze the acceptance factors of user intentions in the application of the Quick Response Indonesia Standard as an electronic wallet payment technology. The user acceptance regarding the Quick Response Indonesia Standard implementation is predicted by user technology acceptance model Unified Theory of Acceptance and Use Technology 2. The object of this study is the Shopeepay and OVO digital wallet user who is domiciled in Jakarta. Data collection techniques by google forms. The independent variables used in this research are all Unified Theory of Acceptance and Use Technology2 model variables except age, gender, experience, and price value using Partial Least Squares-Structural Equation Modelling analysis techniques. The result of this syudy indicate that the facilitating conditions and hedonic motivation affect the user's behavioral intention for using QRIS as their payment technology, and behavioral intention also gives the effect to their use behavior. LPPM 2022-05-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11421 10.30998/faktorexacta.v15i1.11421 Faktor Exacta; Vol 15, No 1 (2022) Faktor Exacta; Vol 15, No 1 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11421/4788 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/16534 2023-03-25T15:11:42Z Faktor_Exacta:ART

Monitoring dan Evaluasi Keamanan Jaringan Dengan Pendekatan System Information and Security Management (SIEM) Ramli, Muhamad Soewito, Benfano Every system produces independent logs. This makes monitoring logs difficult if not done centrally. The research objective is to monitor and evaluate network security using open source-based Security Information and Event Management (SIEM). The research methods include literature studies, SIEM review, observation at the Data and Information System Center (PDSI), simulation of Open Source SIEM implementation by combining devices in real and GNS3 simulation networks, SIEM deployment using Docker, and the final stage of SIEM application evaluation. The implemented SIEM is able to fulfill 84% of the initial requirements. SIEM integrated with Pfsense firewall and Suricata-Intrusion Prevention System (IPS). Monitoring and evaluation features such as detection and alerting, analysis and investigation, compliance and audit, integration and interoperability, monitoring and reporting, support, and maintenance are important parts of SIEM. LPPM 2023-03-23 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16534 10.30998/faktorexacta.v16i1.16534 Faktor Exacta; Vol 16, No 1 (2023) Faktor Exacta; Vol 16, No 1 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16534/5526 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16534/5527 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/21101 2024-05-03T08:17:01Z Faktor_Exacta:ART

Fruit Zone : Media Pembelajaran Interaktif Pengenalan Buah Anak Kelompok Belajar Menggunakan ResNet18 Komariah, Siti Ingefatul Putri, Desti Fitri Aisyah; Politeknik Negeri Jember Rahmawati, Siska Yulia; Politeknik Negeri Jember Fitri, Zilvanhisna Emka; Politeknik Negeri Jember Atmadji, Ery Setiyawan Jullev; Politeknik Negeri Jember Widiastuti, Reski Yulina; Universitas Jember Imron, Arizal Mujibtamala Nanda; Universitas Jember Learning media is very important in supporting learning activities in early childhood. Limited learning media and learning methods that are still centered on the ability and experience of teachers are an obstacle to improving learning at Pos Alamanda 105 Jumerto, Jember. An interactive, cheap, easy and accessible learning media is needed to improve students' abilities, especially in fruit recognition using both Indonesian and English. The solution, researchers used Deep Learning method for interactive learning media of fruit introduction in early childhood. The method used is Convolutional Neural Network with Resnet18 architecture. This research uses 21 types of popular fruits and unique fruits equipped with voice features in Indonesian and English. The total data of 2100 fruit images with a learning rate of 0.0002 and a maximum epoch of 100 wereable to classify the fruit with an accuracy rate of 96% (system training) and 95% (system testing). LPPM Kementerian Pendidikan, Kebudayaan, Riset, Dan Teknologi Republik Indonesia, Direktorat Pembelajaran Dan Kemahasiswaan, Direktorat Jenderal Pendidikan Vokasi dan Politeknik Negeri Jember 2024-05-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21101 10.30998/faktorexacta.v17i1.21101 Faktor Exacta; Vol 17, No 1 (2024) Faktor Exacta; Vol 17, No 1 (2024) 2502-339X 1979-276X 10.30998/faktorexacta.v17i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21101/6604 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/7540 2021-02-22T12:52:52Z Faktor_Exacta:ART

One Vehicle Routing Problem as the Best Solution for a Hangout Catering Company Expansion Plan with Lingo Software One Vehicle Routing Problem as the Best Solution for a Hangout Catering Company Expansion Plan with Lingo Software Borman, Mohammad Riski Oktavia, Mirani Every company that has a desire to expand its working area or can be termed an expansion plan is an indication that the company has the will to continue and develop as well as proof that the company has good business prospects in the future. There are many things that can be done in an expansion effort for the company, including expanding the product marketing area. The expansion of the product marketing area will make the company face the problem of determining the route of product delivery so that it reaches all customers who are expected to pass the shortest mileage. In this studied, we examined the routes that the Hangout Catering Company had to take in order to obtain the best touring to reach the ten places that were expansion targets with three operating scenarios based on the number of vehicles used. The solution to this problem is obtained with the help of Lingo software. Every company that has a desire to expand its working area or can be termed an expansion plan is an indication that the company has the will to continue and develop as well as proof that the company has good business prospects in the future. There are many things that can be done in an expansion effort for the company, including expanding the product marketing area. The expansion of the product marketing area will make the company face the problem of determining the route of product delivery so that it reaches all customers who are expected to pass the shortest mileage. In this studied, we examined the routes that the Hangout Catering Company had to take in order to obtain the best touring to reach the ten places that were expansion targets with three operating scenarios based on the number of vehicles used. The solution to this problem is obtained with the help of Lingo software. LPPM 2021-02-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7540 10.30998/faktorexacta.v13i4.7540 Faktor Exacta; Vol 13, No 4 (2020); 216-231 Faktor Exacta; Vol 13, No 4 (2020); 216-231 2502-339X 1979-276X 10.30998/faktorexacta.v13i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7540/3720 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/7540/1227 Copyright (c) 2020 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/10526 2022-01-26T13:47:30Z Faktor_Exacta:ART

PENGENDALI MONITORING PENYIRAMAN TAMAN BERBASIS ARDUINO MELALUI PARAMETER APRS (AUTOMATIC POSITION REPORTING SYSTEM ) rahman, abdu; Universitas Indraprasta PGRI Ismawan, Fiqih; Universitas Indraprasta PGRI Kondisi cuaca yang kurang menentu menyebabkan beberapa dampak, diantaranya adalah kadang kadar kelembaban tanah kurang atau terlalu tinggi. Kondisi kelembaban tanah sangat mempengaruhi kondisi kesehatan tanaman yang ada di wilayah daerah tersebut. Kesehatan tanaman yang buruk dapat mempengaruhi keindahan taman. Kurangnya keindahan taman dapat menyebabkan berkurang pengunjung baik yang bermukim didekat wilayah taman maupun yang jauh dari taman tersebut. Apabila kondisi kelembaban rendah perlu adanya penyiraman secara langsung untuk menaikan kelembaban. Kondisi tersebut karena penyiraman secara manual menggunakan fungsi manusia perlu untuk meluangkan waktu dan kesabaran. Masalah waktu yang lebih sulit dihindari, hal tersebut karena kesibukan manusia dan lebih terasa cepatnya waktu saat ini. Tujuan penelitian merancang sistem irigasi yang berjalan secara otomatis dengan memonitor kelembaban tanah untuk perawatan taman. Metode penelitian yang akan di gunakan dengan melakukan desain konsep alat pengendali otomatis penyiraman tanaman, observasi berdasarkan pengukuran data sistem aprs internet system, serta mengintegrasikan hasil pantauan data dengan konsep alat pengendali otomatis penyiraman taman. Hasil penelitian yaitu memadukan konsep teknologi otomatis yang berkembang saat ini dengan menggunakan Arduino sebagai alat pengendali penyiraman air dan data dari APRS (Automatic Packet Reporting System), sebagai data pendukung dalam kondisi kelembaban tanah di wilayah taman yang memerlukan sistem otomatis berupa data yang real time. LPPM Fakultas Teknik Ilmu Komputer Universitas Indraprasta PGRI 2022-01-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10526 10.30998/faktorexacta.v14i4.10526 Faktor Exacta; Vol 14, No 4 (2021); 175-184 Faktor Exacta; Vol 14, No 4 (2021); 175-184 2502-339X 1979-276X 10.30998/faktorexacta.v14i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10526/4500 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/14924 2023-01-24T12:06:17Z Faktor_Exacta:ART

Pengembangan E-Modul Interaktif Berbasis Flipbook pada Pembahasan Biologi Ayuardini, Marisha; Universitas Indraprasta PGRI Penelitian ini bertujuan untuk menghasilkan media pembelajaran berupa e-modul interaktif berbasis Flipbook untuk meningkatkan kemampuan pemahaman konsep biologi. Dalam hal ini peneliti mengembangkan media pembelajaran dalam bidang pendidikan yang berintegrasi dengan perkembangan teknologi informasi dan komunikasi. Inovasi media pembelajaran yang dikembangkan adalah membuat modul digital dua dimensi yang dapat membuka halaman layar seolah membaca di layar monitor berbasis Flipbook. Metode Penelitian yang digunakan dalam penelitian ini adalah metode penelitian pengembangan (Research and Develompment) dengan model pengembangan ADDIE (Analyze, Design, Develop, Implementasi dan Evaluate). Modul berbasis Flipbook ini dibuat dengan menggunakan Software Flip PDF Comporate Edition dimana menyajikan teks, gambar, audio, dan video. Hasil penelitian media berbasis Flipbook ini dikatakan layak untuk digunakan berdasarkan validasi dari ahli materi, ahli media, dan ahli bahasa, yaitu dengan rata-rata skor total sebesar 80% untuk penilaian validasi ahli materi, rata-rata skor total sebesar 60% untuk penilaian validasi ahli media, dan rata-rata skor total sebesar 60% untuk penilaian validasi ahli bahasa, yang masing-masing masuk pada kriteria “layak”. Selain itu, sudah dilakukan uji lapangan kepada tiga puluh peserta didik dan mendapatkan skor nilai rata-rata respon peserta didik sebesar 80% dengan katagori “baik”, serta telah dilakukan uji coba efektivitas media dalam meningkatkan kemampuan pemahaman konsep mendapatkan skor nilai rata-rata 0,46 dengan kategori sedang. LPPM 2023-01-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14924 10.30998/faktorexacta.v15i4.14924 Faktor Exacta; Vol 15, No 4 (2022); 259-271 Faktor Exacta; Vol 15, No 4 (2022); 259-271 2502-339X 1979-276X 10.30998/faktorexacta.v15i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14924/5354 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/19564 2024-01-09T11:00:23Z Faktor_Exacta:ART

PENERAPAN METODE CONVOLUTIONAL NEURAL NETWORK UNTUK KLASIFKASI KUALITAS DAGING SAPI PADA APLIKASI BERBASIS ANDROID Asmoro, Phaksi Bangun Solichin, Achmad; Universitas Budi Luhur The surging demand for beef in Indonesia poses a significant challenge for the food industry, leading to fraudulent practices among meat traders. To meet the high consumer demand and gain higher profits, fresh beef is mixed with spoiled meat. Unfortunately, many consumers are unable to distinguish between fresh and spoiled beef, relying solely on the meat's aroma to determine its quality. However, recognizing spoiled beef requires considering other indicators of spoilage. To address this issue, researchers focused on developing a beef quality classification system using the Convolutional Neural Network (CNN) method. The study involved implementing TensorflowLite on Android devices and training the CNN model with deep learning algorithms to recognize visual patterns in beef images. The Android application provides clear and user-friendly classification results. The developed beef quality classification system achieved remarkable accuracy, with a precision of 97%, a recall of 96%, and an f1 score of 97%. With 100 beef images as test data, the system demonstrated an accuracy rate of 95.69%. This advancement is expected to improve the efficiency and quality of beef processing in Indonesia, ensuring consumers receive genuine and safe products LPPM 2024-01-08 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19564 10.30998/faktorexacta.v16i4.19564 Faktor Exacta; Vol 16, No 4 (2023) Faktor Exacta; Vol 16, No 4 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19564/6290 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/5944 2020-12-17T16:05:25Z Faktor_Exacta:ART

OPEN DATA KIT SYSTEM DAN SMARTPHONE ANDROID SEBAGAI SOLUSI PENGUMPULAN DATA RPTRA JAKARTA SELATAN Hermawati, Mercy Muchbarak, Akbar; Universitas Indraprasta PGRI Pengumpulan data merupakan tahap penting dalam setiap melakukan desain atau program penelitian. Saat ini, pada prakteknya pengumpulan data masih banyak menggunakan metode manual yaitu dengan media kertas yang menyebabkan rendahnya kualitas bila volume datanya besar. Perkembangan teknologi informasi dan komunikasi seperti sistem operasi android yang telah mendominasi perangkat mobile di seluruh penjuru dunia. Bahkan ada beberapa tools yang dapat dimanfaatkan untuk pengumpulan data tanpa kertas. Sampai akhir tahun 2019 ini, sudah 60 RPTRA tersebar di beberapa titik lokasi Jakarta Selatan. Namun belum ada satu portal khusus untuk memuat profil dari masing-masing RPTRA tersebut, sehingga sulitnya mendapatkan informasi lengkap seputar RPTRA Jakarta Selatan secara cepat dan akurat. Penelitian ini bertujuan untuk memudahkan pengumpulan data dengan cepat dan berkualitas menggunakan alat dan metode yang memiliki sebuah server terpusat, memudahkan pengumpulan data RPTRA Jakarta Selatan dengan menggunakan Open Data Kit System dan Smartphone Android. Selain itu juga bertujuan untuk menghasilkan aplikasi android yang dapat digunakan sebagai sarana dalam melihat hasil survei data RPTRA Jakarta Selatan. Penelitian ini menggunakan pendekatan penelitian kuantitatif dengan jenis penelitian survei. Menggunakan open data kit (ODK) sebagai tools pengumpulan data RPTRA Jakarta Selatan. Hasil penelitian yaitu penggunaan ODK System dapat membantu proses pengumpulan data menjadi lebih cepat dan mudah untuk diolah karena sudah dalam bentuk digital. Pengumpulan data RPTRA Jakarta Selatan melalui perangkat mobile dapat dilakukan dalam kondisi online maupun offline atau tanpa jaringan internet, sehingga dapat digunakan dalam segala situasi. Hasil lain dari penelitian ini yaitu informasi hasil survei diharapkan dapat dilihat oleh masyarakat luas melaui aplikasi berbasis android yang mana datanya tersaji secara online. LPPM 2020-11-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/5944 10.30998/faktorexacta.v13i3.5944 Faktor Exacta; Vol 13, No 3 (2020) Faktor Exacta; Vol 13, No 3 (2020) 2502-339X 1979-276X 10.30998/faktorexacta.v13i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/5944/3534 Copyright (c) 2020 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/21166 2024-10-30T05:13:35Z Faktor_Exacta:ART

SMART ATTENDANCE WITH FACE ANTI-SPOOFING TECHNOLOGY USING HAAR CASCADE CLASSIFIER Supriatna, Ujang; STMIK IKMI Cirebon Kurnia, Dian Ade; STMIK IKMI Cirebon Suprapti, Tati; STMIK IKMI Cirebon Traditional attendance systems often encounter challenges in efficiently and accurately recording attendance. This research aims to introduce an innovative solution through the development of an intelligent anti-spoofing attendance system based on facial recognition using the Haar Cascade Classifier method. Designed to overcome the inefficiencies in attendance recording, this system ensures the accuracy of educational staff attendance records. Its development method relies on the Haar Cascade Classifier, employing image processing to detect learned object features, particularly focusing on facial recognition. Research findings indicate that the implementation of this system achieves an average accuracy rate of 98.90% in attendance recording. The facial recognition technology ensures reliable attendance recording with confidence levels exceeding 80%, signifying precise facial identification that addresses various challenges and ensures attendance data integrity. Not only does the system identify educational staff with high accuracy, but it also provides prompt responses for efficient attendance logging and verification. Beyond its technical benefits, this study significantly contributes to the development of smarter and more efficient attendance technology. The system plays a crucial role in enhancing the discipline of educational staff at STMIK IKMI Cirebon and streamlining attendance management and evaluation across educational institutions. LPPM Dian Ade Kurnia, STMIK IKMI Cirebon, Department of Informatic 2024-10-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21166 10.30998/faktorexacta.v17i3.21166 Faktor Exacta; Vol 17, No 3 (2024); 262-274 Faktor Exacta; Vol 17, No 3 (2024); 262-274 2502-339X 1979-276X 10.30998/faktorexacta.v17i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21166/7102 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/21166/4396 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/9297 2021-08-10T19:36:16Z Faktor_Exacta:ART

Penerapan Metode Machine Learning untuk Prediksi Nasabah Potensial menggunakan Algoritma Klasifikasi Naïve Bayes Fitrianah, Devi; Universitas Mercu Buana Dwiasnati, Saruni; Universitas Mercu Buana H, Hanny Hikmayanti; Universitas Buana Perjuangan Karawang Baihaqi, Kiki Ahmad; Universitas Buana Perjuangan Karawang Customers are people who trust the management of their money in a bank or other financial service party to be used in banking business operations, thereby expecting a return in the form of money for their savings. To reach information to increase company profits, a method is needed to be able to provide knowledge in supporting the data that the company has. The model can be obtained by using predictive data processing of customer data that is categorized as potential or not potential. Data processing can be done using Machine Learning, namely classification techniques. This technique will produce a churn prediction model for determining the category of customers who fall into the Potential or Not Potential category and find out what accuracy value will be generated by applying the classification technique using the Naïve Bayes Algorithm. The parameters used in this study are Gender, Age, Marital Status, Dependent, Occupation, Region, Information. The data used are 150 data from customers who have participated in the savings program to find out whether the customer is in the Potential or Non-Potential category. The accuracy results generated using this data are 86.17% of the tools used by Rapidminner. LPPM 2021-08-10 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9297 10.30998/faktorexacta.v14i2.9297 Faktor Exacta; Vol 14, No 2 (2021); 92-99 Faktor Exacta; Vol 14, No 2 (2021); 92-99 2502-339X 1979-276X 10.30998/faktorexacta.v14i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9297/4155 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/9297/1593 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/11817 2022-11-01T15:12:13Z Faktor_Exacta:ART

Penerapan Lean Project Management Pada Proyek Pembangunan Water Treatment System Di PT Karya Nurindo Perdana, Surya; (Scopus ID: 57202802444), Teknik Indutri, Universitas Indraprasta PGRI Rahman, Arif; Teknik Indutri, Universitas Indraprasta PGRI Widjajanto, Tulus; Teknik Indutri, Universitas Indraprasta PGRI PT Karya Nurindo merupakan perusahaan yang bergerak dibidang jasa konstruksi pembangunan instalasi pengolahan air. Saat ini PT Karya Nurindo sedang menjalankan proyek pembangunan Water Treatment System di Perum PERURI. Pengerjaan yang sedang dilakukan perusahaan tersebut adalah tanki penyimpanan limbah cair B3. Dalam pengerjaan proyek tersebut terdapat beberapa kendala yang menyebabkan keterlambatan dari jadwal yang sudah direncanakan. Untuk mengurangi kerugian yang timbul maka perlu dilakukan perbaikan, menghilangkan waste dan melakukan percepatan pengerjaan proyek dengan sisa waktu yang masih tersedia. Tujuan penelitian ini adalah untuk mengidentifikasi dan menghilangkan waste yang ada pada proyek pembangunan Water Treatment System, sehingga dalam pelaksanaan proyek dapat terlaksana dengan lebih efektif dan efisien. Untuk mengatasi hal tersebut dilakukan analisis munggunakan metode Lean Project Management (LPM). Dari hasil dan analisis data yang telah dilakukan, diperoleh kesimpulan bahwa waste yang terdapat pada pelaksanaan proyek pembangunan Water Treatment System (tanki penyimpanan limbah cair B3) yang dikerjakan oleh PT Karya Nurindo di Perum PERURI adalah Waste Waiting. Penyebab munculnya Waste Waiting dikarenakan faktor lingkungan dan faktor material. Untuk mengatasi risiko yang terdapat penelitian ini adalah dengan melakukan percepatan, pada pekerjaan ini dilakukan penambahan pekerja dan melakukan pengiriman material dengan jumlah banyak dalam waktu yang bersamaan. LPPM 2022-11-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11817 10.30998/faktorexacta.v15i3.11817 Faktor Exacta; Vol 15, No 3 (2022); 192-199 Faktor Exacta; Vol 15, No 3 (2022); 192-199 2502-339X 1979-276X 10.30998/faktorexacta.v15i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11817/5146 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/17314 2023-11-10T10:43:11Z Faktor_Exacta:ART

Terapan Metode Least Significant Bit untuk Deteksi Keaslian e-Sertifikat Primawati, Alusyanti; Teknik Informatika,FTIK, Universitas Indraprasta PGRI Paramita, Aulia; Teknik Informatika,FTIK, Universitas Indraprasta PGRI Muchbarak, Akbar; (Scopus ID: 57205058978) Universitas Indraprasta PGRI Sulistyohati, Aprilia; Teknik Informatika,FTIK, Universitas Indraprasta PGRI The ease of accessing digital information allows a person to change or manipulate the data contained in the information. Therefore, the security of information or vital data from intruders or unauthorized access is important. One of the cases that are currently happening is the distribution and falsification of information through fake e-certificates. The purpose of this study is to improve security, and check the authenticity and validity of data on e-certificates using steganography techniques with the Least Significant Bit (LSB) method. Steganography is used to disguise confidential information in digital media so that confidential information is difficult to detect by unauthorized parties. The image on the certificate in the form of a pdf file will be inserted with information to validate whether the certificate is genuine or not, by reading the pixels in the image in the file. In this study, the data to be inserted is in the form of a checksum value in the form of 32 hexadecimal characters and also e-certificate information in the form of a JSON string. The results of this study are a website-based application that is capable of checking the authenticity of e-certificates. LPPM 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17314 10.30998/faktorexacta.v16i3.17314 Faktor Exacta; Vol 16, No 3 (2023) Faktor Exacta; Vol 16, No 3 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17314/6118 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/11735 2022-07-08T15:53:35Z Faktor_Exacta:ART

oai:ojs.localhost:article/22342 2024-07-17T04:29:56Z Faktor_Exacta:ART

Komparasi Pengaruh Model Klasifikasi Naive Bayes dan Support Vector Machine Pada Analisis Data Sentimen Di Bidang Pendidikan Fajriah, Riri; Universitas Budi Luhur Kurniawan, Denni; Universitas Budi Luhur Penerapan data mining dalam text mining processing banyak dimanfaatkan dalam penelitian analisis sentimen. Beberapa penelitian analisis sentimen menggunakan model klasifikasi supervised machine learning seperti Naive Bayes dan Support Vector Machine. Tujuan penelitian adalah mengevaluasi bagaimana pengaruh model klasifikasi Naive Bayes dan Support Vector Machine pada analisis sentimen, khususnya dibidang pendidikan. Beberapa penelitian terdahulu banyak mengambil objek penelitian analisis sentimen pada bidang pemasaran, sosial, ekonomi, politik, sehingga analisa penelitian akan membantu memberikan strategi pengembangan penelitian analisis sentimen dibidang pendidikan. Pada bidang bidang pendidikan sumber data yang digunakan misalnya dari opini siswa dan guru terkait capaian pembelajaran. Hasil penelitian menunjukkan model klasifikasi Naive Bayes dan Support Vector Machine dapat memberikan nilai akurasi yang baik dalam penelitian analisis sentimen, namun penggabungan kedua model dengan pendekatan ensemble lebih meningkatkan capaian akurasi. Untuk penelitian anaisis sentimen dibidang pendidikan ada beberapa faktor penting yang perlu diperhatikan seperti kontribusi penelitian, metode implementasi data mining, parameter yang mempengaruhi, evaluasi data dan resiko kegagalan. Semua faktor tersebut diharapkan dapat diperhatikan sebagai conceptual framework yang akan mendukung keberhasilan dalam penelitian analisis sentimen di bidang pendidikan bagi penelitian yang dilakukan di masa mendatang. LPPM 2024-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/22342 10.30998/faktorexacta.v17i2.22342 Faktor Exacta; Vol 17, No 2 (2024); 167-178 Faktor Exacta; Vol 17, No 2 (2024); 167-178 2502-339X 1979-276X 10.30998/faktorexacta.v17i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/22342/6798 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/22342/4724 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/22342/4725 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/12922 2022-08-10T14:47:58Z Faktor_Exacta:ART

Rancang Bangun Sistem Kendali Pintu Pagar Otomatis Berbasis Pengolahan Citra Digital Pelat Nomor Kendaraan Menggunakan Metode Optical Character Recognition (OCR) Alam, Syah; Universitas Trisakti Fauzi, Firman; Sekolah Tinggi Teknologi Indonesia Tjahjadi, Gunawan; Universitas Trisakti Sya’ban, Ridzki Saputro; Sekolah Tinggi Teknologi Indonesia The gate is the main access to enter and exit the vehicle. In general, the gate is opened and closed manually by humans so it takes time and effort. This study proposes the design of an automatic gate control system based on digital image processing of vehicle number plates using the Optical Character Recognition (OCR) method to be able to recognize vehicle number plates. The vehicle number plate image will be recorded by a USB camera and processed using MATLAB to recognize each character on the vehicle number plate. Then the results of processing the vehicle number plate image are compared with the number plate database that has been inputted into the system. If the number plate is registered in the database, MATLAB will forward the command to Arduino Uno to drive the servo motor to open the gate. From the test results, it takes 7 seconds to process the vehicle number plate image processing until the gate is open. The percentage of successful reading of vehicle number plate characters by the MATLAB system is 100% of the 6 number plates tested with an accuracy of 100%. This research can be recommended as an automatic gate control system for security in buildings and homes. LPPM 2022-08-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/12922 10.30998/faktorexacta.v15i2.12922 Faktor Exacta; Vol 15, No 2 (2022) Faktor Exacta; Vol 15, No 2 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i2 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/12922/4915 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/13803 2023-07-31T10:37:27Z Faktor_Exacta:ART

Analisa Perbandingan Penerapan Metode SARIMA dan Prophet dalam Memprediksi Persediaan Barang PT XYZ Analisa Perbandingan Penerapan Metode SARIMA dan Prophet dalam Memprediksi Persediaan Barang PT XYZ Gunawan, Wawan; Universitas Mercu Buana Ramadani, Misbah; Universitas Mercu Buana Determining the right level of inventory is very important because it relates to the flow of money and can affect the performance of an organization. Too much inventory of goods can cause accumulation of storage space (warehouse) and reduce capital. The research will use data on sales of tires and wheels to be predicted using the SARIMA and Prophet methods, then the results will be compared for accuracy using RMSE. Based on the research results, it can be concluded that SARIMA (0, 0, 0)x(0, 1, 1, 12) with an RMSE evaluation result of 3.61 is superior to Prophet in predicting Dunlop product sales with an RMSE evaluation result of 4.02. SARIMA has the advantage in predicting because in the process there are features to find the best parameters to be implemented in the model. Determining the right level of inventory at this time is important because it is related to and can affect the work of an organization. The computerized inventory management system provides more efficient and stable results compared to the manual system, which often results in human error so that the warehouse becomes less efficient. This study compares the application of the SARIMA and Prophet methods in predicting PT XYZ's inventory for a period of 5 months. It is concluded that SARIMA(0,0,0)x(0,1,1,12) is better than Prophet in predicting inventory with RMSE results of 3.61 and 4.02. LPPM 2023-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13803 10.30998/faktorexacta.v16i2.13803 Faktor Exacta; Vol 16, No 2 (2023) Faktor Exacta; Vol 16, No 2 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13803/5823 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/21190 2024-05-03T08:21:20Z Faktor_Exacta:ART

Analisis Trend Topik Penelitian Tesis Pada Program Studi Magister Ilmu Komputer Universitas Budi Luhur Menggunakan Metode Latent Dirichlet Allocation (LDA) Wahyudi, Arief; Universitas Budi Luhur Bayuaji, Luhur; Budi Luhur University Every year, thousands of studies are conducted by researchers from various institutions and places, focusing on various fields and topics. This also applies to thesis research conducted by students of the Master of Computer Science Program at the Faculty of Information Technology, Universitas Budi Luhur. Given the significant amount of research over time at Budi Luhur University's Master of Computer Science Program, it has become increasingly difficult to effectively understand research trends and focus. The purpose of this study is to identify trending thesis research topics in the Master of Computer Science Program at Universitas Budi Luhur. The data used in this research includes thesis research titles conducted from 2016 to 2021. The method used in this research is Latent Dirichlet Allocation (LDA). The results of the study produced the best pass value at 28 and the best number of topics was 5 topics. LDA modeling produces 5 research topics that are trending in the period 2016 to 2021, namely sentiment analysis, data analysis, prediction analysis, decision support systems and machine learning. LPPM 2024-05-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21190 10.30998/faktorexacta.v17i1.21190 Faktor Exacta; Vol 17, No 1 (2024) Faktor Exacta; Vol 17, No 1 (2024) 2502-339X 1979-276X 10.30998/faktorexacta.v17i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21190/6610 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/21190/4432 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/7833 2021-04-27T14:57:10Z Faktor_Exacta:ART

ANALISIS GROUND VIBRATION DENGAN METODE PEAK PARTICLE VELOCITY (PPV) Hadi S, Hari; Universitas Nasional Wati, Erna Kusuma; Universitas Nasional Kristiono, Tomas; Universitas Nasional Measurement of Peak Particle Velocity (PPV) mm / sec in the Sabo dam construction project was carried out using seismic accelerometers. This study is to determine the value of PPV produced by construction equipment and then compared with the BS 6472-2: 2008 standard. The measurement method is carried out based on the applicable rules. PPV measurement results produced by each machine are different. In heavy equipment dump trucks, excavators, and front end loaders show PPV values at distances of 50 m, 100 m, 150 m and 200 m under safe conditions referring to the standard which is still in the range of 0.2 - 0.4 mm / sec. while for the pile driving device, demolition, vibrator pile driver at a distance of 50 meters are in unsafe conditions, because more than the range of 0.2 - 0.4 mm / sec, but at a distance of 100, 150, and 200 m PPV values are at safe conditionKey words: PPV, Ground Vibration, Dam sabo LPPM 2021-03-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7833 10.30998/faktorexacta.v14i1.7833 Faktor Exacta; Vol 14, No 1 (2021); 9-13 Faktor Exacta; Vol 14, No 1 (2021); 9-13 2502-339X 1979-276X 10.30998/faktorexacta.v14i1 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7833/3943 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/9848 2022-07-14T12:04:00Z Faktor_Exacta:ART

Pemanfaatan Application Programming Interface (API) pada Aplikasi Layanan Jasa Perbaikan Kendaraan Bermotor Fitrahriansyah, Ilham Jaman, jajam Haerul; Universitas Singaperbangsa Karawang Perbaikan maupun perawatan kendaraan merupakan salah satu dari berbagai macam jenis pelayanan yang ada pada bengkel motor/ mobil. Para pengguna kendaraan mengalami kesulitan bila tidak ada kontak atau komunikasi dengan bengkel untuk melakukan pemanggilan teknisi. Teknisi yang di panggil membutuhkan waktu lama bila tidak mengetahui jalur atau rute perjalanan untuk sampai lokasi pengendara. Diperlukannya adanya suatu sistem yang berfungsi sebagai pemesanan teknisi, lokasi pengendara dan pelaporan pelayanan. Metodologi meliputi tahap pengumpulan data (studi literatur, observasi, dan wawancara) dilanjutkan ke tahap pengembangan sistem menggunakan metode SDLC dengan pengembangan aplikasi yang dibangun menggunakan model pendekatan Prototype. Pengujian standar aplikasi menggunakan white box testing, black box testing dan juga evaluasi kepada pengguna. Hasil yang didapat adalah seluruh menu dapat berjalan sesuai fungsinya masing-masing, dan hasil evaluasi yang dilakukan dengan survey kepada 30 sampel pelanggan, admin, dan teknisi. Dengan adanya aplikasi ini dapat mengatasi permasalahan pemesanan selama ini, hal tersebut dibuktikan dengan kuisioner dengan rata-rata nilai 7.5 yang artinya “setuju” dengan adanya aplikasi pelayanan jasa teknisi ini. LPPM 2022-05-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9848 10.30998/faktorexacta.v15i1.9848 Faktor Exacta; Vol 15, No 1 (2022) Faktor Exacta; Vol 15, No 1 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9848/4786 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/14991 2023-03-25T15:10:20Z Faktor_Exacta:ART

Penerapan Location Based Service(LBS) Pada Sistem Pencarian Kontrakan Dengan Metode Prototype Hermawan, Dicky; Universitas Pelita Bangsa Wiyanto, Wiyanto; Universitas Pelita Bangsa Wiyatno, Tri Ngudi; Universitas Pelita Bangsa The lack of information about rentals such as descriptions and prices make it difficult for seekers to determine which rental option is in accordance with their wishes and also the price. With the conventional search process, rent seekers inevitably take the time and energy to find rentals according to their wishes, location and of course the price. This study aims to apply the location base service to support the search for rentals that make it easy and according to the wishes of rented seekers in Bekasi Regency as well as a promotional media for rented business owners for household needs, using the main method, namely location base service to solve the problem of finding a rental business that is still ongoing. many shortcomings and the prototype method as a system development method that supports this research. The result of this research is that the koskuappfront application is able to make renting search more efficient in terms of time and cost, as well as collecting rental information in one container that provides rental information. LPPM 2023-03-23 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14991 10.30998/faktorexacta.v16i1.14991 Faktor Exacta; Vol 16, No 1 (2023) Faktor Exacta; Vol 16, No 1 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14991/5522 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/20852 2024-01-09T12:15:29Z Faktor_Exacta:ART

Clustering the K-means Algorithm with the Approach to Student Interpersonal Communication Patterns in Selecting Secondary Schools Wulan, Rayung Widaningsih, Themotia Titi; Universitas Sahid Jakarta Yanuar, Fit; Universitas Sahid Jakarta This research aims to understand students' communication patterns in choosing secondary schools by identifying existing group patterns, and understanding the factors that influence students' decisions in choosing secondary schools. Using the k-means algorithm clustering method, the dataset was obtained from student data, psychological test scores and interpersonal communication in three grade 9 junior high schools in West Jakarta. The dataset obtained was 317, the results of data clearing were 259 students who were eligible to be tested. The results of tests carried out with 4 clusters show an accuracy value close to 0, with cluster 2 having a value of -0.150. The results show that students who choose a secondary school based on their psychological test results and interpersonal communication between parents, homeroom teachers and the school are the dominant values in the continuity of selecting a senior secondary school LPPM 2024-01-08 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/20852 10.30998/faktorexacta.v16i4.20852 Faktor Exacta; Vol 16, No 4 (2023) Faktor Exacta; Vol 16, No 4 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/20852/6294 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/20852/6296 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/20852/4319 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/7254 2021-02-18T12:45:26Z Faktor_Exacta:ART

Analisis Dan Implementasi Metode Earliest Due Date (EDD) Untuk Meminimalisir Keterlambatan Dalam Proses Penjadwalan Perbaikan Kendaraan Rismawati, Nofita; - Trisanto, Dedy; - Abstrak. Penjadwalan layanan perbaikan kendaran yang dilakukan oleh sebagian besar perusahaan otomotif masih belum efektif dan masih menggunakan proses konvensional dengan melakukan perhitungan berdasarkan subjektif karyawan tanpa menggunakan suatu metode penjadwalan tertentu. Permasalahan yang terjadi pada sebagian besar perusahaan otomotif yaitu adanya keterlambatan dalam penyelesaian perbaikan kendaraan customer sehingga sering melewati batas waktu perjanjian penyelesaian kendaraan customer. Permasalahan keterlambatan tersebut terjadi karena belum menggunakan suatu metode penjadwalan tertentu sehingga belum adanya penentuan pekerjaan yang diprioritaskan. Untuk mengatasi masalah tersebut diperlukan suatu metode aturan prioritas yaitu dengan menggunakan metode Earliest Due Date (EDD). Metode ini menjalankan pekerjaan yang memiliki due date yang masih lama setelah pekerjaan dengan due date yang sudah mendekati perjanjian dengan customer. Data yang digunakan merupakan data dari salah satu perusahaan otomotif periode bulan Juni 2020 dengan parameter stall (tempat untuk kendaraan yang diperbaiki) yang digunakan untuk setiap harinya selalu konstan sebanyak 2 stall. Dari hasil perhitungan, menunjukkan bahwa Metode Earliest Due Date (EDD) membantu dalam mengurangi keterlambatan pekerjaan perbaikan kendaraan sehingga dapat meminimalisir kerterlambatan dalam proses penjadwalan perbaikan kendaraan. Kata Kunci: Penjadwalan, Customer, Earliest Due Date (EDD)Abstract. The scheduling of vehicle repair services carried out by most automotive companies is still ineffective and still uses a conventional process by calculating based on employee subjective without using a specific scheduling method. The problem that occurs in most automotive companies is that there is a delay in completing customer vehicle repairs so that they often pass the deadline for the customer's vehicle settlement agreement. The problem of delays occurs because they have not used a specific scheduling method so that there is no prioritized job determination. To solve this problem, a priority rule method is needed, namely by using the Earliest Due Date (EDD) method. This method runs a job that has a due date that is still long after the job with a due date that is close to the agreement with the customer. The data used is data from one of the automotive companies for the period of June 2020 with the stall parameter (the place for the vehicle being repaired) which is used for every day is always constant as much as 2 stalls. From the calculation results, it shows that the Earliest Due Date (EDD) Method helps reduce delays in vehicle repair work so as to minimize delays in the vehicle repair scheduling process. Key words: Scheduling, Customer, Earliest Due Date (EDD) LPPM 2020-11-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7254 10.30998/faktorexacta.v13i3.7254 Faktor Exacta; Vol 13, No 3 (2020) Faktor Exacta; Vol 13, No 3 (2020) 2502-339X 1979-276X 10.30998/faktorexacta.v13i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7254/3536 Copyright (c) 2020 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/24149 2024-10-30T05:13:35Z Faktor_Exacta:ART

Pemanfaatan Chi Square dan Ensemble Tree Classifier pada Model SVM, KNN dan C4.5 dalam Penjualan Online Indriyanti, Prastika; Universitas Mercu Buana Gunawan, Wawan; Universitas Mercu Buana This research aims to assist MSMEs in overcoming problems in online sales. Currently, sellers only prepare stock without knowing how well the products are sold in their market segment. In the city of Tangerang alone, there are 222,602 MSMEs with various product categories. Therefore, besides utilizing offline sales, business actors should also engage in online sales. This research conducts feature selection using the Chi-Square method and Ensemble Tree Classifier to select the top 6 and 10 features. The SVM, KNN, and C4.5 algorithms are used to build prediction models based on the selected features. Using feature selection, it was found that the influential features are Estimated Shipping Cost, Shipping Cost Paid by Buyer, Total Product Price, and Estimated Shipping Cost Discount. The evaluation results using the three algorithms, SVM, KNN, and C4.5, indicate that the highest accuracy value is obtained when using the C4.5 model with data from the ensemble tree classifier with 6 features at 0.86%, followed by the C4.5 model with 10 features, KNN with 6 features, and KNN with 10 features, all of which source data from the ensemble tree classifier with an accuracy value of 0.85%. LPPM 2024-10-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/24149 10.30998/faktorexacta.v17i3.24149 Faktor Exacta; Vol 17, No 3 (2024); 314-322 Faktor Exacta; Vol 17, No 3 (2024); 314-322 2502-339X 1979-276X 10.30998/faktorexacta.v17i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/24149/7107 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/9807 2021-12-24T14:22:10Z Faktor_Exacta:ART

RANCANG BANGUN PROTOTYPE PENGENDALIAN LENGAN ROBOT (ROBOTIC ARM) SEBAGAI PEMINDAH BARANG BERBASIS INTERNET OF THINGS Alam, Syah; Universitas Trisakti Tjahjadi, Gunawan; Universitas Trisakti Yenita, Nur Rahma; Sekolah Tinggi Teknologi Indonesia Supriyadi, Supriyadi; Sekolah Tinggi Teknologi Indonesia This study proposes a prototype design of a robot arm control system based on the Internet of Things (IoT) by utilizing the NodeMCU microcontroller and the Blynk application. The NodeMCU microcontroller functions as a control system combined with four servo motors that are positioned as mechanical drives at the base, shoulder, elbow and grip of the robot arm. The angle settings of each motor are 180 °, 90 °, 60 ° and 90 ° which are used as actuators for lifting, gripping and moving loads. To control the robotic arm, the blynk application can be accessed via smartphone. From the results of the design and testing, it was found that the maximum load that could be moved was 20 grams with a transfer time of 46 seconds and a speed of 0.0054 seconds. The max-imum distance for moving goods is 25 cm and the types of goods being moved are those that have a rough sur-face. This research is useful as a solution for moving goods that can be controlled remotely LPPM 2021-10-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9807 10.30998/faktorexacta.v14i3.9807 Faktor Exacta; Vol 14, No 3 (2021); 140-149 Faktor Exacta; Vol 14, No 3 (2021); 140-149 2502-339X 1979-276X 10.30998/faktorexacta.v14i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/9807/4322 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/14148 2023-01-24T12:06:17Z Faktor_Exacta:ART

Studi Kasus Terhadap Alat Penukar Kalor 127-C PUSRI IV Berbasis Simulasi Program Heat Transfer Research Inc. (HTRI) Dengan Variabel Jumlah Plug dan Material Tube Aurelia, Nucke; Universitas Sriwijaya Cundari, Lia; Universitas Sriwijaya Mangkoto, Winandyo; PT. Pupuk Sriwidjaja (PUSRI) Heat exchanger (HE) is used as a medium for heat exchange between fluids. One of the most critical HE at PUSRI, is the 127-C (Ammonia Refrigerant Condenser) in the PUSRI-IV ammonia unit which is supported by 2 identical HEs, namely 127-CA and 127-CB. This HE serves to condense ammonia gas into liquid ammonia. After evaluating the performance of this HE, there was an average decrease of 31.46%. Therefore, it is necessary to optimize this HE, one of which is through research using the HTRI (Heat Transfer Research Inc.) simulator to see the effect of the number of plugs and tube material replacement. The variable number of plugs used are 17, 250, 500, 750 and 1000 for the 127-CA and 21, 250, 500, 750 and 1000 for the 127-CB. As for the tube material variables, namely Carbon Steel (CS), 304- Stainless Steel (304-SS), and 316- Stainless Steel (316-SS). After simulation and analysis were carried out by considering the factors of heat transfer performance, corrosion resistance and cost-benefit, it was concluded that re-tubing with 304-SS material was the most appropriate choice. The maximum number of plugs for CS material is 1000 pieces while for 304-SS and 316-SS materials it is 750 pieces. Heat exchanger (HE) is used as a medium for heat exchange between fluids. One of the most critical HE at PUSRI, is the 127-C (Ammonia Refrigerant Condenser) in the PUSRI-IV ammonia unit which is supported by 2 identical HEs, namely 127-CA and 127-CB. This HE serves to condense ammonia gas into liquid ammonia. After evaluating the performance of this HE, there was an average decrease of 31.46%. Therefore, it is necessary to optimize this HE, one of which is through research using the HTRI (Heat Transfer Research Inc.) simulator to see the effect of the number of plugs and tube material replacement. The variable number of plugs used are 17, 250, 500, 750 and 1000 for the 127-CA and 21, 250, 500, 750 and 1000 for the 127-CB. As for the tube material variables, namely Carbon Steel (CS), 304- Stainless Steel (304-SS), and 316- Stainless Steel (316-SS). After simulation and analysis were carried out by considering the factors of heat transfer performance, corrosion resistance and cost-benefit, it was concluded that re-tubing with 304-SS material was the most appropriate choice. The maximum number of plugs for CS material is 1000 pieces while for 304-SS and 316-SS materials it is 750 pieces. LPPM Universitas Sriwijaya, PT. Pupuk Sriwidjaja 2023-01-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14148 10.30998/faktorexacta.v15i4.14148 Faktor Exacta; Vol 15, No 4 (2022); 223-233 Faktor Exacta; Vol 15, No 4 (2022); 223-233 2502-339X 1979-276X 10.30998/faktorexacta.v15i4 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/14148/5350 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/19539 2023-11-10T10:41:36Z Faktor_Exacta:ART

ANALISIS KEBERHASILAN STUDI AWAL MAHASISWA MENGGUNAKAN KLASTERISASI K-MEANS Painem, Painem Soetanto, Hari; Universitas Budi Luhur Solichin, Achmad; Universitas Budi Luhur Mahasiswa merupakan salah satu elemen penting dalam perkuliahan di perguruan tinggi. Setiap mahasiswa yang menempuh kuliah di suatu perguruan tinggi tentunya menginginkan dapat lulus tepat waktu dengan memenuhi kualifikasi akademik yang optimal. Demikian juga bagi pihak program studi dan universitas, keberhasilan studi mahasiswa merupakan salah satu indikator penting dalam keberhasilan penyelenggaraan pendidikan di perguruan tinggi. Analisis keberhasilan studi mahasiswa seharusnya dilakukan secara berkala mulai dari awal studi hingga akhir studi. Hasil analisis keberhasilan studi dapat dijadikan dasar dalam pengambilan keputusan dan evaluasi program pembelajaran bagi program studi maupun universitas. Namun demikian, melakukan analisis keberhasilan studi mahasiswa pada sebuah perguruan tinggi dengan jumlah mahasiswa yang cukup banyak terkadang sulit dilakukan dan cukup rumit Pengelola universitas dan/atau program studi seringkali kesulitan dalam menyusun program pembelajaran yang tepat sasaran bagi mahasiswa dalam rangka menghasilkan lulusan yang memiliki kemampuan akademik yang optimal dan lulus tepat waktu. Untuk membantu ketua program studi dalam melakukan analisis keberhasilan studi awal mahasiswa adalah dengan metode klusterisasi k-means. Berdasarkan analisa keberhasilan studi awal mahasiswa menggunakan kalsterisasi K- means maka mahasiswa yang masuk ke klaster 0 adalah 22,6 % atau sebanyak 3055 mahasiswa, sedangkan yang masuk ke klaster 1 adalah 69,5 % atau sebanyak 9405 mahasiswa dan yang masuk ke dalam klaster 2 adalah 7,9 % atau 1066 mahasiswa LPPM 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19539 10.30998/faktorexacta.v16i3.19539 Faktor Exacta; Vol 16, No 3 (2023) Faktor Exacta; Vol 16, No 3 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19539/6113 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/24388 2024-10-30T05:13:35Z Faktor_Exacta:ART

COMPARISON OF DIABETES DISEASE CLASSIFICATION MODELS USING LOGISTIC REGRESSION AND RANDOM FOREST ALGORITHMS nabila, putri; Universitas Buana Perjuangan Karawang Mutoi Siregar, Amril; Universitas Buana Perjuangan Karawang Faisal, Sutan Pratama, Adi Rizky Diabetes is a lifelong chronic disease that disrupts blood sugar regulation. Diabetes is a life-threatening condition that, if left untreated, can lead to death and other health problems. Several medical tests, including the glycated hemoglobin (A1C) test, blood sugar test, oral glucose tolerance test, and fasting blood sugar test, can be used to detect diabetes. According to statistics, high glucose levels are one of the problems associated with diabetes. This study aims to categorize patients into diabetic and non-diabetic groups using specific diagnostic metrics included in the dataset. 1500 patient records with 9 attributes and 2 classes were used by the researchers. The study used machine learning techniques, including Logistic Regression and Random Forest, along with Confusion Matrix and Receiver Operating Characteristics (ROC) assessment. The Random Forest method produced results of 97% accuracy, 97% precision, 100% recall, and 98% f1-score, indicating that the accuracy level seems good but can still be improved. Based on the accuracy findings, Random Forest is the most effective strategy of Logistic Regression. LPPM 2024-09-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/24388 10.30998/faktorexacta.v17i3.24388 Faktor Exacta; Vol 17, No 3 (2024); 221-227 Faktor Exacta; Vol 17, No 3 (2024); 221-227 2502-339X 1979-276X 10.30998/faktorexacta.v17i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/24388/7098 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/13254 2022-08-10T14:49:22Z Faktor_Exacta:ART

Prediksi Daya Output Sistem Pembangkit Listrik Tenaga Surya (PLTS) Menggunakan Regresi Linear Berganda Bramasto, Suryo; Program Studi Teknik Informatika, Institut Teknologi Indonesia Khairiani, Dian; BALAI BESAR TEKNOLOGI KONVERSI ENERGI, Badan Pengkajian dan Penerapan Teknologi (BPPT) The power generated by Solar Power Plants (Pembangkit Listrik Tenaga Surya/PLTS) from time to time is fluctuating due to the influence of weather and other external conditions. This study predicts the output power of PLTS Sumalata in North Gorontalo Regency with data analytics on datasets obtained from measurements at 2 plants in PLTS Sumalata. Data analytics to predict the output power of PLTS Sumalata is using a multiple linear regression approach, which is applied by implementing the Cross-industry standard for data mining (CRISP-DM) process model. The tools used are the Weka 3.0 application and Jupyter Notebook with the Python programming language. With data analytics using Weka 3.0 on datasets obtained from measurements at 2 plants in PLTS Sumalata, multiple linear regression equations were obtained as well as evaluation of prediction results using Correlation Coefficient (CC), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Relative Absolute Error (RAE), and Root Relative Squared Error (RRSE). The equation formed from the prediction of the output power in Plant 1 is Y = -22216632810.1123 - 771640073.1888 X1 + 2349039057.8254 X2 -25796134709.3552 X3. While the equation formed from the prediction of the output power in Plant 2 is Y = -2784.107 + 300.0146 X1 – 173.7016 X2 + 21773.3845 X3. Based on the test, the correlation coefficient on the Plant 1 dataset is 0.52 and the Plant 2 dataset is 0.92. Those can be concluded that the irradiation data, module temperature, and ambient temperature have a significant effect of 52% on the output power generated in the PLTS system at Plant 1 and 92% on Plant 2. Then the MAE, RMSE, RAE, and RRSE values in the Plant 1 dataset are higher than Plant 2, while the relationship between the independent variables and the dependent variables in the Plant 2 dataset is stronger than the Plant 1 dataset. In order to improve the accuracy of the prediction that can be used for evaluating the performance of the PLTS system, measurement data with a minimum measurement duration of one year is needed to be able to represent seasonal conditions throughout the year, such as the dry season, rainy season, and extreme weather conditions. LPPM 2022-08-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13254 10.30998/faktorexacta.v15i2.13254 Faktor Exacta; Vol 15, No 2 (2022) Faktor Exacta; Vol 15, No 2 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i2 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13254/4920 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/17067 2023-07-31T10:56:04Z Faktor_Exacta:ART

Algoritma K-Means Untuk Mengetahui Minat Siswa Terhadap Jurusan Teknik Informatika mardika, putri dina There are already many information technology-based companies in the capital city, many job vacancies may be opened because they require experts with an educational background in informatics engineering. The research was conducted on YMIK 2 Jakarta high school students who concentrated on science and social studies. YMIK 2 High School students are familiar with information technology devices because there is a computer lab as a student facility for conducting computer learning activities. And there is an internet network in the form of free wifi at school. Researchers used data mining techniques with the K-Means algorithm and RapidMiner tools to process data to produce some conclusions about groupings related to whether or not YMIK 2 Jakarta High School students are interested in the Informatics Engineering major. The researcher divided the clusters into 2 groups consisting of cluster_0 which means students who are interested in informatics engineering and cluster_1 which means students who are not interested in informatics engineering. The data set used in this study was 50 data, according to the students participating in SMA YMIK 2 Jakarta. From the results of this study, it is known that students who are interested in majoring in informatics engineering are more numerous than students who are not interested in majoring in informatics engineering based on the k-means clustering algorithm. LPPM 2023-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17067 10.30998/faktorexacta.v16i2.17067 Faktor Exacta; Vol 16, No 2 (2023) Faktor Exacta; Vol 16, No 2 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17067/5825 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/17067/3395 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/20625 2024-07-17T04:29:56Z Faktor_Exacta:ART

Application of Data Mining to Prediction of New Students' Interested Departements With an Approach Naive Bayes Algorithm Harsanti, Niken; Universitas Indraprasta PGRI Wibowo, Arief; Universitas Budiluhur Jakarta This research aims to apply data mining techniques using the Naïve Bayes algorithm to predict new students' majors. Choosing a major is an important decision in college, and accurate predictions can help new students make better decisions. In this study, we collected historical data about past students, including information about academic values, interests, and other factors that influence major selection. The Naïve Bayes algorithm is used to process this data and produce a prediction model that can identify majors that best suit the characteristics of new students. The results of data processing for new students obtained accuracy values with the Naïve Bayes algorithm model of 98.55%, precision of 99.97%, and recall of 98.55%. The naive Bayes algorithm model obtained can be implemented in the form of an application designed to predict new students' majors in determining the study program they will take. The Naïve Bayes algorithm is able to provide fairly accurate predictions, which can be used as a guide for new students in choosing their major. This research makes a positive contribution to the development of data mining applications in the field of higher education, with the potential to help students and universities increase the efficiency of major selection. The Naïve Bayes algorithm is able to provide fairly accurate predictions, which can be used as a guide for new students in choosing their major. This research makes a positive contribution to the development of data mining applications in the field of higher education, with the potential to help students and universities increase the efficiency of major selection. The Naïve Bayes algorithm is able to provide fairly accurate predictions, which can be used as a guide for new students in choosing their major. This research makes a positive contribution to the development of data mining applications in the field of higher education, with the potential to help students and universities increase the efficiency of major selection. LPPM 2024-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/20625 10.30998/faktorexacta.v17i2.20625 Faktor Exacta; Vol 17, No 2 (2024); 131-140 Faktor Exacta; Vol 17, No 2 (2024); 131-140 2502-339X 1979-276X 10.30998/faktorexacta.v17i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/20625/6794 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/20625/4241 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/8482 2021-08-10T19:38:34Z Faktor_Exacta:ART

Processing The Ground Motion Signal Recording Using Correction Instrument Method Wati, Erna Kusuma; Universitas Nasional The instrument correction method is a way to eliminate interference with the signal from the recording instrument response. Signal processing by the instrument correction method using the inverse filter method created using the MATLAB program. In this research using Honshu earthquake data, Japan with Mw 7.4 (dated September 5, 2004) recorded by the MERAMEX seismometer type L4C-3D type short seismometer and Japan Tohoku-Oki earthquake with a strength of Mw 9.0 (March 11, 2011) the data from four seismic stations in Padang, West Sumatra with a DS-4A type short-period seismometer. From the research known, the signal can clearly show the phase of the P and S waves. This can help to determine the parameters of the hypocenter, receiver function, moment tensors, studies of . The surface wave phase can be reconstructed well. This is very useful for studies using surface wave data, moment tensor solutions, seismic wave dispersion studies. Based on the amplitude of the instrument correction results compared with theoretical data, the gain or amplification . LPPM 2021-08-10 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/8482 10.30998/faktorexacta.v14i2.8482 Faktor Exacta; Vol 14, No 2 (2021); 55-63 Faktor Exacta; Vol 14, No 2 (2021); 55-63 2502-339X 1979-276X 10.30998/faktorexacta.v14i2 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/8482/4151 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/26562 2025-02-25T08:18:00Z Faktor_Exacta:ART

Learning object reusability evaluation on the free national e-learning system Risaf, Karin A.; Universitas Gunadarma Khalida, Rakhmi; Universitas Bhayangkara Jakarta Raya Supono, Riza Adrianti; Universitas Gunadarma Kegunaan ulang dianggap sebagai karakteristik penting dari konsep objek pembelajaran sebagai gagasan utama untuk desain konten pembelajaran digital modern, karena fakta bahwa mengembangkan materi pendidikan yang berkualitas memiliki harga mahal dalam hal waktu dan sumber daya, itulah sebabnya mengapa dapat menggunakan kembali materi berkualitas yang sudah ada akan menghasilkan keuntungan pedagogis dan ekonomis. E-Learning standardisasi dan penilaian kesesuaian diharapkan dapat menjadi pilihan bagi mahasiswa, dosen, dan profesional Universitas untuk mempelajari tentang standar dan standardisasi. Evaluasi dilakukan untuk menentukan apakah objek pembelajaran dalam sistem e-learning dapat digunakan kembali atau tidak berdasarkan metrik kegunaan ulang dengan variabelnya seperti kohesi, kopling, ukuran dan kompleksitas, portabilitas pendidikan dan portabilitas teknis. Variabel-variabel tersebut dihitung dengan metrik berorientasi objek yang telah diimplementasikan ke objek pembelajaran. Implementasi metrik menunjukkan bahwa hasil kohesi dan kopling objek pembelajaran adalah baik dengan ukuran dan portabilitas pendidikan objek pembelajaran dalam tingkat sedang, juga objek pembelajaran portabel secara teknis yang berarti objek pembelajaran sistem e-learning dapat digunakan kembali LPPM 2025-02-11 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/26562 10.30998/faktorexacta.v17i4.26562 Faktor Exacta; Vol 17, No 4 (2024); 366-376 Faktor Exacta; Vol 17, No 4 (2024); 366-376 2502-339X 1979-276X 10.30998/faktorexacta.v17i4 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/26562/7389 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/26562/5742 Copyright (c) 2025 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/11741 2022-07-14T12:03:17Z Faktor_Exacta:ART

IMPLEMENTASI ALGORITMA COLLABORATION FILTERING DALAM WEBSITE E-COMMERCE (STUDI KASUS TOKO INDRI COLLECTION) Rizky, Fajar Gunawan, Wawan; Universitas Mercu Buana teknologi informasi dan ilmu pengetahuan mengalami pengembangan dan semakin maju, Saat ini yang berkembang adalah situs belanja online, situs belanja online lebih popular dengan sebutan E-Commerce. Perkembangan situs belanja online membuat pelaku usaha memulai menjual barangnya melalui situs belanja online. E-Commerce merupakan tempat suatu kegiatan jual-beli yang di lakukan secara online antara pelanggan dan penjual tanpa harus bertemu langsung melalui situs atau website.Toko Indri Collection memasarkan dan menjual barang menggunakan media sosial, memasarkan dan menjual barang di sosial media sangat tidak aman untuk penjual dan pelanggan. Toko Indri Collection masih melakukan pencatatan secara manual dengan cara mencatat di buku. Cara seperti ini membutuhkan waktu yang lama untuk mencari data transaksi penjualan dan juga merekomendasikan barang kepada pelanggan. Dengan pembuatan website dan menggabungkan algoritma Collaborative Filtering dapat membantu penjualan agar dapat menginformasikan barang berkualitas berdasarkan rating pada produk. Dengan collaborative filtering menghasilkan prediksi tertingi yaitu dengan angka 5 dan 3.966 LPPM 2022-05-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11741 10.30998/faktorexacta.v15i1.11741 Faktor Exacta; Vol 15, No 1 (2022) Faktor Exacta; Vol 15, No 1 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11741/4785 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/16486 2023-03-27T14:37:02Z Faktor_Exacta:ART

Comparison of Classification Algorithms for Predicting Indonesian Fake News using Balanced and Imbalanced Datasets Karima, Sayidati; Gunadarma University Mutiara, Achmad Benny; Gunadarma University Kemajuan teknologi informasi memberikan dampak yang besar, seperti penyebaran berita online. Namun, kabar yang tersebar belum tentu benar adanya. Dalam beberapa penelitian, pendeteksian berita hoax telah dilakukan. Namun, terdapat perbedaan hasil dari beberapa algoritma yang digunakan. Oleh karena itu, dalam penelitian ini dilakukan perbandingan antara algoritma Logistic Regression, Naïve Bayes, Random Forest dan Support Vector Machine untuk memprediksi berita hoax khusus Indonesia dengan dataset seimbang dan tidak seimbang. Tahapan perancangan sistem dimulai dari pengumpulan dataset, pelabelan data, pre-processing, pembobotan TF-IDF, klasifikasi model hingga pengujian. Hasil akurasi tertinggi baik dari jumlah dataset yang tidak seimbang maupun dataset yang seimbang didapatkan dari SVM dengan perbandingan 80:20. Dataset tidak seimbang memiliki akurasi 85,47% dan F1-score 90% dan dataset seimbang memiliki akurasi 84,36% dan F1-score 84,80%. Pada penelitian ini dataset tidak seimbang mendapatkan hasil akurasi yang lebih baik dengan menggunakan algoritma SVM dan jika jumlah dataset yang menjadi target kelas utama lebih banyak maka akan memberikan hasil yang lebih baik. LPPM Gunadarma University 2023-03-23 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16486 10.30998/faktorexacta.v16i1.16486 Faktor Exacta; Vol 16, No 1 (2023) Faktor Exacta; Vol 16, No 1 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i1 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/16486/5536 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/21164 2024-05-03T08:17:39Z Faktor_Exacta:ART

Peramalan Nilai Tukar Rupiah Terhadap Dolar Singapura dengan Pendekatan Average Based Fuzzy Time Series Markov Chain Rahmah, Syifa Ur Putri, Ayu Pratika; Department of Statistic, Universitas Hasanuddin, Indonesia Siswanto, Siswanto; Department of Statistic, Universitas Hasanuddin, Indonesia Kalondeng, Anisa; Department of Statistic, Universitas Hasanuddin, Indonesia Exchange rates, representing a country's currency value in terms of another, signify currency relationships between nations. Indonesia's strong economic ties with Singapore see the Singapore Dollar boasting the highest exchange rate against the Indonesian Rupiah in Asia. The Rupiah-Singapore Dollar exchange rate is marked by fluctuations, necessitating precise forecasts. One effective forecasting method is the average-based Fuzzy Time Series (FTS) Markov Chain. This method calculates intervals based on averages and leverages the Markov Chain concept, employing a transition probability matrix to enhance accuracy. The average-based FTS Markov Chain predicts the Rupiah-Singapore Dollar exchange rate from May 16, 2023, to October 13, 2023, delivering an impressively low Mean Absolute Percentage Error (MAPE) of 0.3642%. Notably, the forecast for October 14, 2023, is 11.583.73. Consistently, this method, blending interval formation through FTS and probability transition matrix from the Markov Chain, provides reliable forecasts. These insights are invaluable for decision-makers, empowering them to proactively address potential fluctuations that might contribute to inflationary pressures on Indonesia's economy. LPPM 2024-05-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21164 10.30998/faktorexacta.v17i1.21164 Faktor Exacta; Vol 17, No 1 (2024) Faktor Exacta; Vol 17, No 1 (2024) 2502-339X 1979-276X 10.30998/faktorexacta.v17i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21164/6605 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/21164/4395 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/7569 2021-02-18T00:15:09Z Faktor_Exacta:ART

SISTEM BERBASIS CLOUD COMPUTING UNTUK IDENTIFIKASI RESEP DOKTER “BARSEP” Saputra, Irwansyah SARYOKO, ANDI; STMIK Nusa Mandiri WIJAYA, GANDA; STMIK Nusa Mandiri TRISIANA, MEILYNDA; STMIK Nusa Mandiri MULYANA, ASEP; STMIK Nusa Mandiri BAYANI, DANDI YUSBIAL; STMIK Nusa Mandiri WINATA, DHARMA; STMIK Nusa Mandiri KHOIRUNNISAK, VILSAFA; STMIK Nusa Mandiri A doctor's prescription is a doctor's written request to the pharmacist to prepare and give medicine to the patient. Prescriptions are made according to the needs of the patient after the doctor has examined and diagnosed the patient. However, doctor’s writing on a prescription that considered unclear can cause errors when compounding / preparing the drug and using prescribed drugs. In fact, the cure rate and life expectancy of patients is directly proportional to the administration of the right medicine. This study aims to prevent errors in the process of identification of prescription drugs by pharmacists. The technology used is cloud computing with the PHP 7.1.3 programming language, Laravel framework, and database storage using MySQL. BarSep application works by adding QR Code on recipe paper. The QR Code contains patient examination information including patient data, prescription drugs, and diagnoses, so that when the pharmacist scans the QR Code, the system will display all patient information that has been inputted by the doctor at the time of the examination. The results obtained from the implementation of the BarSep application at the Rapha Farma Pharmacy is BarSep applications effective for tackling errors in reading doctor's prescriptions that can save patients from medication errors. A doctor's prescription is a doctor's written request to the pharmacist to prepare and give medicine to the patient. Prescriptions are made according to the needs of the patient after the doctor has examined and diagnosed the patient. However, doctor’s writing on a prescription that considered unclear can cause errors when compounding / preparing the drug and using prescribed drugs. In fact, the cure rate and life expectancy of patients is directly proportional to the administration of the right medicine. This study aims to prevent errors in the process of identification of prescription drugs by pharmacists. The technology used is cloud computing with the PHP 7.1.3 programming language, Laravel framework, and database storage using MySQL. BarSep application works by adding QR Code on recipe paper. The QR Code contains patient examination information including patient data, prescription drugs, and diagnoses, so that when the pharmacist scans the QR Code, the system will display all patient information that has been inputted by the doctor at the time of the examination. The results obtained from the implementation of the BarSep application at the Rapha Farma Pharmacy is BarSep applications effective for tackling errors in reading doctor's prescriptions that can save patients from medication errors. LPPM STMIK Nusa Mandiri 2021-02-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7569 10.30998/faktorexacta.v13i4.7569 Faktor Exacta; Vol 13, No 4 (2020); 232-242 Faktor Exacta; Vol 13, No 4 (2020); 232-242 2502-339X 1979-276X 10.30998/faktorexacta.v13i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/7569/3719 Copyright (c) 2020 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/11268 2022-01-26T13:48:33Z Faktor_Exacta:ART

Penerapan Fuzzy Sugeno Orde Satu dalam Prediksi Pembelian Fitrianah, Devi; Universitas Mercu Buana Gunawan, Wawan; Universitas Mercu Buana Sari, Anggi Puspita; Universitas Bina Sarana Informatika Given the rapid advancement of information technology has a great influence in the fields of industry and services. This brings changes in competition between companies, so that company players must always create various techniques to survive. This study aims to assist SMEs in making purchases of the products they sell so that there is no excess stock. This research is calculated using the Fuzzy Sugeno algorithm with a system inference method that can be applied to determine the prediction of the number of purchases of goods. The prediction generated for the test data at week 30 is 60 pcs and this is less when compared to the real data, namely 70 pcs so that it can avoid overstock. Furthermore, the prediction results from the test data at week 21 to week 30 are tested to determine the error rate using the MAPE method, so that the result is 31.67%, and that means that the test is considered reasonable (reasonable). LPPM 2022-01-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11268 10.30998/faktorexacta.v14i4.11268 Faktor Exacta; Vol 14, No 4 (2021); 185-193 Faktor Exacta; Vol 14, No 4 (2021); 185-193 2502-339X 1979-276X 10.30998/faktorexacta.v14i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/11268/4501 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/13356 2023-01-24T12:06:17Z Faktor_Exacta:ART

Pengembangan Sistem Informasi RPTRA Info Menggunakan Metode Prototype Hermawati, Mercy; Universitas Indraprasta PGRI Muchbarak, Akbar; Universitas Indraprasta PGRI RPTRA Info merupakan aplikasi berbasis Android yang digunakan untuk mengetahui informasi lokasi serta sarana dan prasarana yang ada di RPTRA se Jakarta Selatan. Data berupa profil singkat RPTRA beserta foto-foto kondisi sarana dan prasarana yang ada di dalamnya diperoleh dengan cara melakukan survey secara langsung ke lokasi RPTRA. Di masa pandemi Covid19 ini kegiatan di RPTRA dibatasi, sehingga terkadang tidak mengizinkan warga masuk selain petugas. Hal ini tentu saja membuat proses pembaharuan informasi dengan cara survey langsung ke lokasi menjadi terhambat.Untuk dapat selalu memberikan informasi terkini terkait sarana dan prasarana yang ada di RPTRA Jakarta Selatan, maka perlu dibuatkan sebuah sistem informasi yang dapat mengelola data di masing-masing RPTRA oleh masing-masing pengelola RPTRA itu sendiri. Namun diperlukan metode yang tepat dalam merancang sistem tersebut agar dapat sesuai dengan keinginan dari masing-masing stakeholder, dalam hal ini terdiri dari Suku Dinas Pemberdayaan, Perlindungan Anak Dan Pengendalian Penduduk (PPAPP) Jakarta Selatan beserta para pengelola RPTRA yang tersebar di seluruh Jakarta Selatan. Metode yang digunakan yaitu menggunakan metode Prototype, dimana peneliti akan membuat sebuah prototype berdasarkan kebutuhan awal sistem. Hasil rancangan berupa prototype ini dipresentasikan ke seluruh stakeholder dan hanya perlu sedikit penyesuaian mengikuti masukan-masukan dari para stakeholder. Setelah mendapat masukan, selanjutnya dirumuskan masukan mana saja yang akan dieksekusi. Sehingga kemudian dilakukan pembuatan atau penyempurnaan sistem tersebut. Dengan cara seperti ini, dapat mempercepat proses pembuatan sistem mengingat jumlah stakeholder yang cukup banyak yaitu pengelola dari 62 RPTRA dan juga minimnya pemahaman stakeholder mengenai Pengembangan Sistem Informasi. LPPM 2023-01-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13356 10.30998/faktorexacta.v15i4.13356 Faktor Exacta; Vol 15, No 4 (2022); 272-282 Faktor Exacta; Vol 15, No 4 (2022); 272-282 2502-339X 1979-276X 10.30998/faktorexacta.v15i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13356/5355 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/19670 2024-01-09T14:47:39Z Faktor_Exacta:ART

Analisis Model Matematika dan Simulasi Pada Penyebaran Hepatitis Non HepA-E Akut di Indonesia Ristiawan, Rifki; Informatika UNINDRA Wahyudi, Farrell Selvia, Noni Acute Non-HepA-E Hepatitis is a disease that causes symptoms of acute hepatitis without a clear cause. To see the spread of this disease, this study developed the SIR epidemic model into SEIR by adding a population of exposed or latent individuals. This model divides the population into four classes; class of susceptible individuals, exposed individuals, infected individuals and recovered individuals. From the model, the disease-free equilibrium point () and endemic equilibrium point () and the basic reproduction number () are obtained. The results of the analysis concluded that the disease-free equilibrium point is locally asymptotically stable when . The simulation results showed that when the disease will disappear and when the disease will become an epidemic. The simulation results showed that the parameter () is the most influential parameter on the value of (). Then it was concluded that to suppress the spread of Acute Non-HepA-E Hepatitis, the effort that could be done is to limit contact between susceptible individuals and exposed and infected individuals. LPPM Department of Informatic, Universitas Indraprasta PGRI, Indonesia 2024-01-08 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19670 10.30998/faktorexacta.v16i4.19670 Faktor Exacta; Vol 16, No 4 (2023) Faktor Exacta; Vol 16, No 4 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i4 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19670/6293 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/19670/6297 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/6295 2020-12-17T16:05:44Z Faktor_Exacta:ART

Sistem Informasi Pendaftaran Anggota Baru Pada Koperasi Simpan Pinjam Mekar Mandiri Jaya Kustian, Nunu Koperasi Simpan Pinjam Mekar Mandiri Jaya dalam proses penerimaan anggota baru masih belum optimal dan secara konvensional dengan mengisi data diri calon anggota ke dalam form yang tersedia kemudian menyerahkan ke bagian keuangan yang akan diteruskan kepada kepala koperasi. Tujuan pembuatan aplikasi penerimaan anggota baru pada koperasi Simpan Pinjam Mekar Mandiri Jaya untuk menghasilkan sistem yang lebih baik dengan menerapkan metode komputerisasi dengan pengembangan sistem menggunakan model waterfall agar pendataan anggota baru dan lama lebih mudah, dan kegiatan simpan pinjam dapat mengurangi kesalahan pada saat perhitungan dan kehilangan dokumen yang diakibatkan oleh manusia sehingga sangat memabntu bagi pihak koperasi dan anggota baru dalam bertransaksi. LPPM 2020-11-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/6295 10.30998/faktorexacta.v13i3.6295 Faktor Exacta; Vol 13, No 3 (2020) Faktor Exacta; Vol 13, No 3 (2020) 2502-339X 1979-276X 10.30998/faktorexacta.v13i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/6295/3535 Copyright (c) 2020 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/23248 2024-10-30T05:13:35Z Faktor_Exacta:ART

DEVELOPMENT OF AN E-COMMERCE PLATFORM USING EXTREME PROGRAMMING METHODOLOGY Maulana, Affan; Universitas Lampung Mardiana, Mardiana; Universitas Lampung Pradipta, Rio Ariesta; Universitas Lampung The pervasiveness of information technology has reshaped human lifestyles, including shopping practices. Andalas Store, a prominent bookstore, has experienced a decrease in customer visits. Consequently, this research endeavours to establish an e-commerce platform for Toko Andalas utilizing Extreme Programming (XP) and the MERN Stack to broaden customer reach and expand market presence. The e-commerce platform is constructed leveraging the XP software development methodology and undergoes rigorous testing encompassing unit testing, black box testing, Lighthouse, and the System Usability Scale. The research outcomes validate the successful development and testing of the Toko Andalas e-commerce platform, highlighting its website performance in responsiveness, accessibility, adherence to best practices, and SEO optimization. The platform also encompasses comprehensive functionalities, including product search, shopping cart, and online payment. LPPM 2024-10-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/23248 10.30998/faktorexacta.v17i3.23248 Faktor Exacta; Vol 17, No 3 (2024); 275-286 Faktor Exacta; Vol 17, No 3 (2024); 275-286 2502-339X 1979-276X 10.30998/faktorexacta.v17i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/23248/7103 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/10325 2021-12-24T14:22:10Z Faktor_Exacta:ART

ANALISIS SENTIMEN PENGARUH PEMBELAJARAN DARING TERHADAP MOTIVASI BELAJAR DI MASA PANDEMI MENGGUNAKAN NAIVE BAYES DAN SVM Ariansyah, Ariansyah; Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Kusmira, Mira; UNIVERSITAS NUSA MANDIRI The COVID-19 pandemic in Indonesia has had a huge impact on the education sector. Where it is today, it must implement and adapt a new learning model called online. motivation in learning is very important because it can improve achievements. In this case there are many pros and cons about online learning, many people's opinions on social media, especially Twitter about the influence of online learning on learning motivation. This study aims to analyze the influence between online learning and learning motivation. Public opinion on Twitter is used as a sentiment analysis to find out what people think about online learning on learning motivations whether positive or negative. The data used are tweets in indonesian with the keywords "online learning", "distance learning" and "motivational learning", with the number of datasets as many as 455 tweets are classified into 2 parts namely agreement and disagreement. The classification in this study used naive bayes classification algorithm method and Support Vector Machine (SVM) by preprocessing data using tokenize, transform case, filtering and stemming. Data is processed using rapidminer application. The highest accuracy result of this study was by the classification algorithm method support vector machine (SVM) with accuracy 97.22%, precision 94.72%, recall 100% and error 2.78%. LPPM 2021-10-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10325 10.30998/faktorexacta.v14i3.10325 Faktor Exacta; Vol 14, No 3 (2021); 100-106 Faktor Exacta; Vol 14, No 3 (2021); 100-106 2502-339X 1979-276X 10.30998/faktorexacta.v14i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10325/4323 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/13706 2022-11-01T15:12:13Z Faktor_Exacta:ART

Perancangan Aplikasi Perbaikan Citra Digital Pada Hasil Screenshot Dengan Menggunakan Metode Multiscale Retinex dan Median Filter Putra, Noga Adi; Universitas 0amulang Amalia, Resti; Universitas Pamulang Advances in technology today cannot be kept away from people's lives, because basically technology is built to provide convenience to the community. One example is in the field of digital images, digital images are a representation of the light intensity function in a discrete field in a two-dimensional plane, digital images can also be a source of information other than text, sound and video. However, sometimes the image can also experience a decrease in quality caused by noise, too contrasting colors, blurring, and so on. A distorted image is usually caused by poor image capture, poor lighting, low pixel resolution on the camera, and poor image capture capabilities. This is what underlies the improvement in digital images, digital image quality improvements can be done by various methods, one of which is the Multiscale Retinex and Median Filter methods. The advantages of the Multiscale Retinex method are that it can increase the brightness and color of digital images, especially those that tend to be dark, and the Median Filter method can reduce the disturbance that often occurs in digital images, namely noise. With the two methods used to improve the image, a digital image will look better with a degree and level of color that tends to be evenly distributed. The process begins by entering the test image with *.jpg file format into the program then processed by the Multiscale Retinex and Median Filter methods, then the initial image can be compared with the resulting image using a histogram. From the research that the author did, it resulted in a digital image processing application that can improve brightness and reduce noise in digital images. LPPM 2022-11-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13706 10.30998/faktorexacta.v15i3.13706 Faktor Exacta; Vol 15, No 3 (2022); 180-191 Faktor Exacta; Vol 15, No 3 (2022); 180-191 2502-339X 1979-276X 10.30998/faktorexacta.v15i3 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13706/5147 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/17504 2023-11-10T10:46:54Z Faktor_Exacta:ART

Application of 2DPCA and SOM Algorithms to Identification of Digital Signature Ownership Norhikmah, Norhikmah Signature Is one of the proofs for ratification, one of which is a thesis document, with the development of the when conventional signatures have begin to switch to digital signatures, where digital signatures already have a legal umbrella in Indonesia, currently Covid is still hitting Indonesia, forcing some agencies change the ratification of a document using a digital signature, so that it can provide an opening for falsifying digital signature ratification. Therefore, an application is needed to identify the ownership of a digital signature image, with the first research stage is to collect a digital signature dataset in the form of a signature image or take a dataset from a published legal document, an example of a second stage publication manages the image processing with grayscale first to get extra features and then analyzes the extra feature image using 2DPCA, and identification To get the best matching of image units using the Single Organizing Maps (SOM) method. the results of this study are using the 2DPCA algorithm and SOM to identify ownership of digital signatures, with 84 correct and incorrect test results, from a total dataset of 91 patterns. And get the highest accuracy value of 92.3% at a 20000 translation and a rate of 0.9. LPPM UNIVERSITAS AMIKOM YOGYAKARTA 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17504 10.30998/faktorexacta.v16i3.17504 Faktor Exacta; Vol 16, No 3 (2023) Faktor Exacta; Vol 16, No 3 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i3 eng https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/17504/6117 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/17504/3475 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/22408 2024-07-17T04:29:56Z Faktor_Exacta:ART

Komparasi Metode Grey GM (1.1) Dan Grey Verhulst Untuk Prediksi Harga Sembako Zahro, Diah Ayu Fatimatus; Universitas PGRI Ronggolawe Muqtadir, Asfan Suryanto, Andik Adi; Universitas PGRI Ronggolawe This research explores the significance of basic commodities (sembako), such as rice and sugar, as essential necessities, with a focus on price fluctuations influenced by factors like seasonal variations and weather conditions. The pressing issue of rising food demand amid Indonesia's population growth is exacerbated by price fluctuations. The study utilizes grey forecasting method, specifically GM (1.1) and grey Verhulst, to predict the prices of basic commodities in East Java. The comparative results indicate that grey Verhulst excels in forecasting the prices of certain commodities, such as Premium Rice, while GM (1.1) proves more effective for the sugar category. This finding comes from an analysis of the ARPE value that shows the accuracy of the model in the price prediction. The research aims to contribute to addressing the challenges of price changes and instability in basic commodity prices influenced by seasonal factors. The lowest error rate for grey Verhulst is 1.9471% for premium rice, with the highest at 64.535% for sugar. For GM (1.1), the lowest error rate is 2.184% for medium rice, and the highest is 6.633% for premium rice. LPPM 2024-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/22408 10.30998/faktorexacta.v17i2.22408 Faktor Exacta; Vol 17, No 2 (2024); 179-187 Faktor Exacta; Vol 17, No 2 (2024); 179-187 2502-339X 1979-276X 10.30998/faktorexacta.v17i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/22408/6799 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/22408/4748 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/10629 2022-08-17T18:30:09Z Faktor_Exacta:ART

Text Mining of PeduliLindungi Application Reviews on Google Play Store Saputra, Irwansyah Djatna, Taufik; IPB University Siregar, Riki Ruli A.; IPB University Kristiyanti, Dinar Ajeng; Fakultas Teknik dan Informatika, Universitas Multimedia Nusantara Yani, Hasbi Rahma; UIN Imam Bonjol Padang Riyadi, Andri Agung; Universitas Nusa Mandiri Aplikasi PeduliLindungi merupakan aplikasi buatan pemerintah indonesia untuk melakukan pelacakan dan penghentian penyebaran Covid-19. Ulasan terkait aplikasi tersebut tidak seluruhnya baik, hal ini dibuktikan dengan beragamnya peringkat bintang yang diberikan pengguna sehingga terjadinya kesulitan dalam melihat sentimen positif atau negatif terkait aplikasi tersebut. Penelitian ini bertujuan untuk mengklasifikasi ulasan mengenai aplikasi PeduliLindungi kepada dua kelas, yakni sentimen positif dan sentimen negatif. Algoritma klasifikasi yang digunakan adalah klasifikasi Naive Bayes Classifier (NBC). Hasil Menunjukkan Accuracy 85%, Precision 77,7%, Recall 98%, dan F1-Score 86,7%. LPPM 2022-08-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10629 10.30998/faktorexacta.v15i2.10629 Faktor Exacta; Vol 15, No 2 (2022) Faktor Exacta; Vol 15, No 2 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10629/4916 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/15900 2023-07-31T11:08:03Z Faktor_Exacta:ART

Klasifikasi Citra Penyakit Daun Cabai Menggunakan Algoritma Learning Vector Quantization Siswipraptini, Puji Catur Catur; Institut Teknologi PLN Haris, Abdul; Institut Teknologi PLN Sari, Winda Novita The problem often occurs in chili leaves is organisms that interfere with chili plants which can reduce chili production. There are chili plant diseases that are difficult for farmers to recognize by using their eyes and without using tools. The purpose of this study was to produce a model capable of identifying chili leaf diseases based on leaf colour in order to make it easier for farmers to identify chili leaf diseases, especially Phytophthora, Anthracnose, and Cercospora diseases, using the Learning Vector Quantization (LVQ) classification algorithm. Data was collected in the form of digital images of 30 chili leaves which were processed by resizing and transforming RGB to HSV which then proceeded to Canny Edge detection process with the aim of getting patterns from images of chili leaves. The result of testing LVQ algorithm using a confusion matrix get an accuracy of 80%, the precision value of 80%, recall value of 82%, and f-1 score of 81%. LPPM 2023-07-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/15900 10.30998/faktorexacta.v16i2.15900 Faktor Exacta; Vol 16, No 2 (2023) Faktor Exacta; Vol 16, No 2 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i2 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/15900/5826 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/21624 2024-05-03T08:21:52Z Faktor_Exacta:ART

Sistem Pendukung Keputusan Penerimaan Fotografer Pada Widya Photography Dengan Metode AHP Isnaini, Kurniati Ismawan, Fiqih; Universitas Indraprasta PGRI Widiyatun, Fita; Universitas Indraprasta PGRI Widya Photography merupakan salah satu usaha di bidang jasa fotografi yang berada di wilayah Jakarta Timur. Adapun rumusan masalah dari penelitian ini adalah ketika melakukan rekruitmen calon fotografer, Widya Photography masih dilakukan secara manual dengan menggunakan media kertas. Hal ini tentunya kurang akurat dan optimal. Penelitian ini bertujuan untuk meningkatkan kualitas pelayanan fotografi pada Widya Photography, maka dibuatlah sistem pendukung keputusan penerimaan fotografer pada Widya Photography dengan Metode Analytical Hierarchy Process (AHP) yaitu metode yang digunakan untuk mengevaluasi dan membuat keputusan multi-kriteria, setelah itu akan dilakukan penilaian melalui hasil perangkingan dari perhitungan perbandingan beberapa kriteria dan sub-kriteria. Hal ini dilakukan agar dalam proses penerimaan fotografer menjadi lebih akurat dan optimal. LPPM 2024-05-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21624 10.30998/faktorexacta.v17i1.21624 Faktor Exacta; Vol 17, No 1 (2024) Faktor Exacta; Vol 17, No 1 (2024) 2502-339X 1979-276X 10.30998/faktorexacta.v17i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/21624/6611 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/8630 2021-04-27T14:57:10Z Faktor_Exacta:ART

EVALUASI KUALITAS APLIKASI SISTEM INFORMASI MANAJEMEN KEIMIGRASIAN (SIMKIM) VERSI 2.0 BERBASIS WEB MENGGUNAKAN METODE HUMAN ORGANIZATION TECHNOLOGY FIT (Studi Kasus pada Kantor Imigrasi) Bakri, Arham; Gunadarma University Ridwan, Anggraeni; Universitas Gunadarma Immigration office one of the organization implementing information system integration and automation called the immigration management information system (SIMKIM) Version 2.0 for passport services. An evaluation need to find how the system is implemented, the level of success, as far as to which the system contributes to the organizations that use it. SIMKIM Version 2.0 application have three main component namely human organization and technology. The result of the evaluation indicate technology component include system quality getting value 3,24 (good), information quality getting value 3,09 (good), and service quality getting value 3,21 (good). Human component including system user getting value 3,18 (good), user satisfaction getting value 3,07 (good), and the benefits getting value 3,15 (good), and organization structure getting value 3,22 (good). The overall component SIMKIM Version 2.0 implementation obtained value of 3,16 good interpretation based on HOT Fit method. LPPM 2021-03-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/8630 10.30998/faktorexacta.v14i1.8630 Faktor Exacta; Vol 14, No 1 (2021); 14-21 Faktor Exacta; Vol 14, No 1 (2021); 14-21 2502-339X 1979-276X 10.30998/faktorexacta.v14i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/8630/3944 Copyright (c) 2021 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/10265 2022-07-14T11:59:08Z Faktor_Exacta:ART

Penerapan QR Code pada Website E-commerce PT. Bravo Satria Perkasa dengan Algoritma Reed-Solomon Code dan Regression Linear Fatimah, Dian; Mercu Buana University Pengelolaan atau manajemen stok yang baik sangat dibutuhkan dalam penjualan, khususnya penjualan dalam skala besar. PT.Barvo Satria Perkasa merupakan perusahaan yang masih melakukan pengelolaan stok barang secara manual, dimana pengeloaan secara manual memiliki resiko selisih stok yang cukup besar. Salah satu solusi untuk mengurangi resiko selisih stok yaitu dengan pengelolaan secara digital. Bentuk dari pengelolaan secara digital yang dituju yaitu penggunaan QR Code pada website E-Commerce dengan algoritma Reed-Solomon Code. Penggunaan algoritma Reed-Solomon Code pada aplikasi berfungsi untuk men-generate QR Code, dimana akan terjadi proses scan barang sebelum dilakukannya proses packing pada penjualan offline, guna menandai produk, baik yang sudah dikirim maupun yang belum dikirim. Selain sebagai error detection Reed-Solomon Code juga bertugas sebagai error correction. LPPM Mercu Buana University 2022-05-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10265 10.30998/faktorexacta.v15i1.10265 Faktor Exacta; Vol 15, No 1 (2022) Faktor Exacta; Vol 15, No 1 (2022) 2502-339X 1979-276X 10.30998/faktorexacta.v15i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/10265/4783 Copyright (c) 2022 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/15108 2023-03-25T15:10:39Z Faktor_Exacta:ART

KOMPARASI KLASTER PENGANGGURAN TERBUKA DI INDONESIA SEBELUM DAN SAAT PANDEMI COVID-19 MENGGUNAKAN K-MEAN CLUSTERING Maliqi, Raihan; Univrsitas Nusa Mandiri Falgenti, Kursehi; (Scopus ID 57189267771) Universitas Nusa Mandiri Jakarta Open unemployment is a productive workforce of secondary education and higher education graduates who have not worked at all. The Indonesian Statistics Bureau (BPS) routinely publishes provincial open unemployment (TPT) data per semester. Many studies have analyzed TPT data by exploring new knowledge using data mining methods with cluster analysis techniques. Researchers have investigated the TPT data cluster under normal conditions before the COVID-19 pandemic. This study aims to find new knowledge from TPT data by comparing the TPT data cluster analysis results before the pandemic (2018-2019) with TPT data during the pandemic (2020-2021). Data mining techniques used are cluster analysis and the k-mean algorithm. The cluster analysis results are regional clusters with low and high unemployment rates before and during COVID-19. In addition, another finding is the movement from high to down clusters. Other interesting results are Covid-19 has the most impact on high unemployment in Aceh, North Sumatra, West Sumatra, Riau Islands, DKI Jakarta, West Java, Banten, East Kalimantan, North Sulawesi, Maluku, and West Papua. Anticipatory steps of the high open unemployment rates in 11 provinces, local government could design the program or policy that could support the BLT policy by the central government. LPPM 2023-03-23 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/15108 10.30998/faktorexacta.v16i1.15108 Faktor Exacta; Vol 16, No 1 (2023) Faktor Exacta; Vol 16, No 1 (2023) 2502-339X 1979-276X 10.30998/faktorexacta.v16i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/15108/5523 https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/downloadSuppFile/15108/2939 Copyright (c) 2023 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0

oai:ojs.localhost:article/13914 2024-05-03T08:13:43Z Faktor_Exacta:ART

Rancangan Sistem Kendali Penyiraman dan Pemupukan untuk Perawatan Tanaman Tembakau pada Pusat Budidaya Di Klaten Jawa Tengah Haryono, Faza Juan; Universitas Indraprasta PGRI Primawati, Alusyanti; Universitas Indraprasta PGRI Awaludin, Aulia Ar Rakhman; Universitas Indraprasta PGRI Penggunaan teknologi IoT mampu menjadi salah satu solusi untuk membantu petani tembakau dalam mengontrol tanaman tembakau. Tujuan dari penelitian ini adalah untuk membangun sebuah sistem dan alat yang dapat mempermudah pekerjaan petani tembakau dalam melakukan penyiraman dan pemupukan pada tanaman tembakau melalui aplikasi android. Metode yang digunakan adalah Waterfall meliputi analisis kebutuhan, desain, implementasi, pengujian, dan perawatan sistem. Pembangunan sistem menggunakan Internet of Things, aplikasi android dan mikrokontroler NodeMCU ESP 8266 untuk mengontrol sensor DHT 11, Soil Moisture YL-69, menyalakan water pump dan mengirimkan data ke aplikasi android untuk menginformasikan temperature dan suhu udara pada tanaman, serta dapat mengontrol penyiraman dan pemupukan. Sistem ini juga dapat menampilkan data grafik mengenai temperature dan kelembaban tanah disetiap waktunya. Pengujian sistem dengan metode blackbox, tahapan dimulai memeriksa fungsi masing-masing komponen sistem sensor untuk mengetahu data pada tanaman tembakau. Semua fungsidapat berjalan dengan baik dan melakukan penyiraman dan pemupukan secara merata. Implementasi dari sistem ini akan mempercepat dan mempermudah pekerjaan para petani tembakau dengan melakukan penyiraman dan pemupukan menggunakan aplikasi android sebagai kontrol IoT yang terhubung ke media tanam tembakau LPPM 2024-05-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13914 10.30998/faktorexacta.v17i1.13914 Faktor Exacta; Vol 17, No 1 (2024); 1-8 Faktor Exacta; Vol 17, No 1 (2024); 1-8 2502-339X 1979-276X 10.30998/faktorexacta.v17i1 ind https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/13914/6602 Copyright (c) 2024 Faktor Exacta http://creativecommons.org/licenses/by-nc/4.0 9c76320271dfadd045debd1b5562bc54