Penerapan Metode Klasifikasi Naive Bayes untuk Analisis Sentimen terhadap Undang-Undang ITE di Media Sosial Twitter

Dimas Fajar Fiandaru
Yoannes Romando Sipayung

ELSE (Elementary School Education Journal) : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar
Vol 9 No 2 (2025): AUGUST

The Electronic Information and Transactions Law has caused much debate in Indonesia regarding freedom of expression. Through social media, especially Twitter, people often express their opinions about this law. This study uses the naive bayes classification method to analyze comments on Twitter regarding the Electronic Information and Transactions Law (ITE). The results will be compared with five research journals that use similar or different methods for sentiment analysis on social media. The data used in this study are comments, tweets, and posts on Twitter social media. This study found that the naive bayes classification method on google collab provides 94% accuracy in classifying sentiment. This comparison shows that this method is competitive with other methods such as LSTM, K-NEAREST NEIGHBOR ALGORITHM, SVM, LSTM and BiLSTM, NAIVE BAYES ALGORITHM.