ANALISIS SENTIMEN CYBERBULLYING PADA KOMENTAR TIKTOK TERKAIT ISU REMAJA MENGGUNAKAN NAÏVE BAYES CLASSIFIER SEBAGAI DASAR PENGUATAN LITERASI DIGITAL
Keywords:
Analisis Sentimen, Cyberbullying, TikTok, Naïve Bayes, Literasi DigitalAbstract
Cyberbullying merupakan salah satu permasalahan yang sering muncul pada media sosial dan dapat berdampak negatif terhadap kesehatan mental remaja. TikTok sebagai platform yang banyak digunakan remaja memungkinkan terjadinya interaksi melalui komentar yang mengandung sentimen positif maupun negatif. Penelitian ini bertujuan untuk menganalisis sentimen komentar TikTok terkait isu remaja menggunakan algoritma Multinomial Naïve Bayes sebagai dasar penguatan literasi digital. Penelitian menggunakan pendekatan kuantitatif dengan data sebanyak 1.508 komentar TikTok. Tahapan penelitian meliputi pengumpulan data, pelabelan, preprocessing teks (case folding, cleaning, tokenizing, stopword removal, dan stemming), transformasi data menggunakan TF-IDF, serta klasifikasi menggunakan Multinomial Naïve Bayes. Evaluasi model dilakukan menggunakan confusion matrix, accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa 55,2% komentar tergolong sentimen positif dan 44,8% sentimen negatif. Model menghasilkan nilai accuracy sebesar 69,33%, precision sebesar 68,14%, recall sebesar 83,73%, dan F1-score sebesar 75,14%. Hasil tersebut menunjukkan bahwa Multinomial Naïve Bayes memiliki kemampuan yang cukup baik dalam mengklasifikasikan sentimen komentar TikTok dan mengidentifikasi potensi cyberbullying. Temuan penelitian ini dapat dimanfaatkan sebagai dasar pengembangan program literasi digital dan upaya pencegahan cyberbullying pada kalangan remaja.
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Copyright (c) 2026 Ari Ardana, M. Saleh, M. Akbar Riwanto, Muh. Rasyid Ridha (Author)
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