Analisis Trend Topik Penelitian Tesis Pada Program Studi Magister Ilmu Komputer Universitas Budi Luhur Menggunakan Metode Latent Dirichlet Allocation (LDA)

Arief Wahyudi; Luhur Bayuaji

doi:10.30998/faktorexacta.v17i1.21190

Analisis Trend Topik Penelitian Tesis Pada Program Studi Magister Ilmu Komputer Universitas Budi Luhur Menggunakan Metode Latent Dirichlet Allocation (LDA)

Arief Wahyudi^(1*), Luhur Bayuaji⁽²⁾

(1) Universitas Budi Luhur
(2) Budi Luhur University
(*) Corresponding Author

Abstract

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.

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DOI: http://dx.doi.org/10.30998/faktorexacta.v17i1.21190