PEMBANGUNAN MODEL PEMILIHAN PEMINATAN JURUSAN PADA SEKOLAH MENENGAH ATAS DENGAN ALGORITMA FUZZY C MEANS: STUDI KASUS SMA PGRI 3 JAKARTA

AMBAR TRI HAPSARI(1*)

(1) Teknik Informatika, Fakultas Teknik, Matematika dan Ilmu Pengetahuan Alam
(*) Corresponding Author

Abstract


The trend is happening today, many students simply follow the opinion of parents, friends. With just base this opinion and without reviewing a student’s ability to make decision that are very contrary to the interest and talents. Consequently happens after that, that is laziness learning and decreased overcome the problems of error in choosing this department takes a decision support system capable of performing calculations of value, and intereset owned by senior high school students to help determine the appropriate department. The system uses fuzzy logic used c-means (FCM) which requires some input of the average value of report cards semester and second semester, and the average value of tests of academic potential. With this approach, students are expected to be able to choose an appropriate high school majors.

 Key Word: Decision Support System, Election Departement, interest, algorythm, Fuzzy C-Means.


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References


Agus Naba. 2009, Belajar Cepat Fuzzy Logic Menggunakan Matlab. Yogyakarta: Andi

Anniestya. 2012. Perbedaan clustering dengan html. http://anniestya.blogspot.com/2012/05/perbedaan-custering-dengan.html. 12 Juni 2014.

Bahar. 2011. Penentuan Jurusan Sekolah Menengah Atas dengan Algoritma Fuzzy C-Means, Semarang: Universitas Dian Nuswantoro

Departemen Pendidikan Nasional, 2004, Panduan Penilaian Penjurusan Kenaikan Kelas dan Pindah Sekolah, Jakarta : Direktorat Pendidikan Menengah Umum.

Hartati, Sri Kusuma Dewi. Neuro Fuzzy, Integrasi Sistem Fuzzy dan Jaringan Syaraf. Yogyakarta: Graha Ilmu.

Irfan. Nasrulloh. 2011. Model Pemilihan Jurusan SMK Teknologi Informasi Dengan Pendekatan Logika Fuzzy. Jakarta: Universitas Budi Luhur

Klir, George J, Yuan, Bo. 1995. Fuzzy Sets and Fuzzy Logic, Theory and Application. Prentice Hall International, Inc

Kusrini. 2006. Algoritma Data Mining, Yogyakarta: Andi

Kusumadewi, S, 2004. Aplikasi Logika Fuzzy Untuk Pendukung Keputusan, Yogyakarta: Graha Ilmu

Laboratorium Data Mining FTI UII. Data mining modul Clustering. http://www.ss354.com/wp-content/uploads/2014/03/Data-Mining-Modul-Clustering-Modul-Clustering.pdf . 12 Juni 2014.

Larose, Daniel T. 2005. Discovering Knowledge in Data: An Introduction to Data Mining. John Willey & Sons, Inc.

Mangkoesapoetra, Arief. 2004. Statistika: Analisa Multivariat. Seri metode Kuantitatif. Jakarta: STMIK Nusa Mandiri

Maman. 2006. Sistem Pendukung Keputusan: Model Penentuan Siswa Teladan pada SMK YP-KARYA 1 Tangerangdengan Pendekatan Logika Fuzzy. Jakarta: Universitas Budi Luhur

Marimin dan Nurul. 2010. Aplikasi Teknik Pengambila Keputusan dalam Rantai Pasok,Bogor: Cetakan 1 IPB Press.

Pramudiono,I. 2006. Apa Itu Data Mining ? Dalam http://datamining.japati.net/- bin/indodm.cgi. 28 Mei 2012.

Sianipar, R.H. 2013. Pemrograman MatLab Dalam Contoh dan Penerapan. Bandung : Informatika Bandung

Sri dan Hari. 2010. Aplikasi Logika Fuzzy untuk Pendukung Keputusan. Yogyakarta : Edisi 2 Graha Ilmu.

Sumanto. 2011. Penerapan Fuzzy C-Means (FCM) dalam pemilihan Peminatan Tugas Akhir Mahasiswa, STMIK Nusa Mandiri.

Widodo, Prabowo. P, dan Rahmadya Trias Handayanto. 2012. Penerapan Sotf Computing Dengan Matlab. Bandung : Rekayasa Sains.




DOI: http://dx.doi.org/10.30998/faktorexacta.v9i1.738

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