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All Journal Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan
Dhea Putri Aprilyana
Program Studi Informatika, Universitas Bhayangkara Jakarta Raya, Bekasi, Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT

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Implementasi Algoritma Naïve Bayes dan Algoritma C4.5 Untuk Melakukan Analisis Sentimen terhadap Ulasan Komentar Pengguna TikTok di Google Play Store Dhea Putri Aprilyana; Wowon Priatna; Siti Setiawati
Jurnal Pelita Teknologi Vol 19 No 1 (2024): Maret 2024
Publisher : Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/pelitatekno.v19i1.2488

Abstract

TikTok is a popular application among young people. TikTok was an application initially launched in China before landing in Indonesia at the end of 2017. Unfortunately, the popularity of TikTok stems from personal lack of self-image, for example wearing sexy clothes, dancing in erotic and inappropriate moves. This is based on many positive and negative comments from TikTok users. So we need a way to automatically classify reviews through sentiment analysis. The purpose of this study is to classify TikTok user comments on Google Play Store using Naive Bayes and C4.5 algorithms. This study used 1330 data, of which 602 data were negative and 728 data were positive. The results show that the Naive Bayes algorithm produces accuracy values ​​of 79.00%, 79.00% precision, 78.00% recall, and 78.00% F1 score. The C4.5 algorithm produces 68.00% accuracy, 68.00% precision, 68.00% recall, and 68.00% F1 score. We can conclude that the Naive Bayes algorithm is the best algorithm compared to the C4.5 algorithm. The Naive Bayes algorithm achieves an accuracy value of 79.00%.
Co-Authors Priatna , Wowon Siti Setiawati