ANALISIS SENTIMEN ULASAN GAME EFOOTBALL 2024 PADA PLAYSTORE MENGGUNAKAN ALGORITMA NAÏVE BAYES - Nur Rahman, Rohim; Rahim, Abdul; Joko Pranoto, Wawan (JURNAL ILMIAH INFORMATIKA, 2025)
The rapid development of technology has made access to digital entertainment easy. This includes online games such as eFootball, which has been downloaded more than 100 million times and received mixed reviews on the Google Play Store. This study examines the sentiment of eFootball user ratings using the Naive Bayes algorithm. The methodological process includes data selection, pre-processing, transformation using CountVectorizer and TF-IDF, and classification with Naive Bayes. From 1500 reviews on Google Play Store, the Naive Bayes model obtained 85% accuracy, 85% precision, 86% repeatability rate, and 85% F1 score. The results of this study show that Naive Bayes is effective for classifying sentiment from eFootball game ratings.