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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA IKRA-ITH Informatika : Jurnal Komputer dan Informatika JURIKOM (Jurnal Riset Komputer) Bulletin of Computer Science Research Jurnal Informatika, Komputer dan Bisnis (JIKOBIS) Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi Media Journal of General Computer Science (MJGCS) Jurnal Pengabdian Masyarakat Unama
Pareza Alam Jusia, Pareza Alam
STIKOM Dinamika Bangsa, Jambi
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering

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Journal : Bulletin of Computer Science Research

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Peningkatan Performa Naive Bayes dengan Fitur Chi-Square pada Analisis Sentimen Komentar Pengguna Aplikasi Netflix Jusia, Pareza Alam; Pahlevi, Riza; Pardamean Simanjuntak, Daniel Sintong; Jasmir
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.532

Abstract

This study discusses sentiment analysis using the Naïve Bayes algorithm with Chi-Square. The purpose of this study is to determine the effect of Chi-Square feature selection on the performance of the Naïve Bayes algorithm in analyzing document sentiment. The research data was taken from Netflix Application user comments. Testing was carried out by analyzing document sentiment with and without Chi-Square feature selection. Furthermore, it was evaluated using the accuracy, precision, and recall methods. The results of this study are that the addition of CS features to NB significantly improves all evaluation metrics, especially recall and F1-score, indicating that additional features help improve the model's ability to understand data. The combination of NB + CS with a 70:30 split gives the best results, making it the optimal choice.
Co-Authors ., Amroni Abdul Rahim Agus Nugroho, Agus Agus Siswanto Ali Sadikin Amroni Arvita, Yulia Aulia, M. Farhan Beny Dodi Sandra Errissya Rasywir Febrina Mardayani, Risa Gunardi Gunardi Gusriyanti, Dwi Ayu Halim, Rina Hartiwi, Yessi Hendrawan Hendrawan Herti Yani, Herti Irfan, Fadhel Muhammad ISW, Ibnu Sani Wijaya Jasmir Jasmir, Jasmir Juliana Juliana Kurniabudi, Kurniabudi Mery NOVIANTO, YUDI Nurul Marwiyah, Siska OPHELIA, CHANDY Pahlevi, M. Riza Paramitha, Cindy Pardamean Simanjuntak, Daniel Sintong Pebrianto, Feri Putra, Rafi Septiandi Reflika, Mutiara Riza Pahlevi, Riza ROBY SETIAWAN Rofi’i, Imam SAYID ACHMAD MAULANA Sharipuddin Sharipuddin, Sharipuddin Stefani, Dina Maria Tesaloniki, Viola Wardani, Muhammad WIJAYA, IBNU SANI WILLY RIYADI Yovi Pratama