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All Journal Jurnal Algoritma
Dheo Laurenz Purba
Universitas Prima Indonesia
Computer Science & IT

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Klasifikasi Sentimen Ulasan GoFood di Google Play Store dengan Metode Naive Bayes Dwi Diva Teresia Situngkir; Anita; Dheo Laurenz Purba
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3479

Abstract

GoFood is a food delivery feature within the Gojek application that has received numerous user reviews on the Google Play Store. The high volume of reviews creates a need for efficient automated sentiment analysis. This study aims to classify the sentiment of GoFood reviews using the Multinomial Naive Bayes method with TF-IDF weighting. A total of 1,649 Indonesian-language reviews were collected through web scraping from the Google Play Store, then processed through preprocessing and sentiment labeling stages, with an 80 percent training data and 20 percent testing data split. The evaluation results show an accuracy of 78.14 percent, with negative sentiment precision of 0.76 and recall of 1.00, as well as positive sentiment precision of 0.96. The low positive recall was caused by data imbalance and the absence of data balancing techniques such as SMOTE. The scientific contribution of this study is the provision of a sentiment map based on Multinomial Naive Bayes and TF-IDF as a reference for GoFood service evaluation and the development of Indonesian-language text sentiment analysis.
Co-Authors Anita Anita Dwi Diva Teresia Situngkir