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All Journal Jurnal Nasional Teknologi Informasi dan Aplikasinya
Putu Steven Belva Chan
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Computer Science & IT Engineering

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Deteksi Hate Speech pada Unggahan Media Sosial dengan Naive Bayes Menggunakan Seleksi Fitur Chi-Square Putu Steven Belva Chan; Ida Ayu Gde Suwiprabayanti Putra
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 1 (2024): JNATIA Vol. 3, No. 1, November 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2024.v03.i01.p20

Abstract

In the digital age, social media's pervasive use has revolutionized global communication but also introduced challenges like hate speech. This study proposes a Multinomial Naive Bayes model optimized with Chi-square feature selection to detect hate speech efficiently from large-scale social media data. Leveraging machine learning, this approach aims to combat harmful content by identifying relevant text features crucial for distinguishing hate speech from non-hate speech. The study utilizes TF-IDF for feature extraction and Chi-square for feature selection, showing significant performance improvements in hate speech detection. The Chi-square feature selection model yielded average precision, recall, F1-score, and accuracy values of 92%, 92%, 91%, and 92% respectively. In contrast, the model without feature selection achieved values of 89%, 89%, 88%, and 89% for the same metrics. Results demonstrate enhanced accuracy, precision, recall, and F1-score across various hate speech categories. 
Co-Authors Ida Ayu Gde Suwiprabayanti Putra