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All Journal Jurnal Sintaks Logika (JSilog)
Sasongko, Mohammad Umar Sasongko
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Computer Science & IT

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Analisis Analisis Sentimen Ulasan eFootball pada Google Play Store Menggunakan Multinomial Naive Bayes dan Support Vector Machine Sasongko, Mohammad Umar Sasongko; Irawan, Bambang
Jurnal Sintaks Logika Vol. 6 No. 1 (2026): Januari 2026
Publisher : Fakultas Teknik Universitas Muhammadiyah Parepare

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31850/jsilog.v6i1.4282

Abstract

In the digital era, the use of mobile applications is increasing, so it is important to understand user satisfaction and dissatisfaction with the applications used. One of the popularmobile games in Indonesia is eFootball 2026, which has a lot of reviews from players on the Google Play Store. The large number of reviews allows sentiment analysis to be carried out to find out user opinions on the quality of the application. This study aims to analyze the sentiment of eFootball application user reviews using the Multinomial Naive Bayes method and Support Vector Machine. Review data is processed through the stages of text preprocessing, feature extraction using TF-IDF, and class imbalance handling with SMOTE. Model evaluation was carried out using accuracy, precision, recall, and F1-score metrics. The results showed that the Multinomial Naive Bayes method produced an accuracy of 76.72%, while the Support Vector Machine obtained an accuracy 74.92%, with relatively balanced precision, recall, and F1-score values. Based on these results, it can be concluded that the Multinomial Naive Bayes method has a better performance in analyzing the sentiment of eFootball app reviews on the Google Play Store and can be used as a basis for evaluation for future app development.
Co-Authors Bambang Irawan