Jurnal Algoritma
Vol 23 No 1 (2026): Jurnal Algoritma

Klasifikasi Sentimen Ulasan GoFood di Google Play Store dengan Metode Naive Bayes

Dwi Diva Teresia Situngkir (Universitas Prima Indonesia)
Anita (Universitas Prima Indonesia)
Dheo Laurenz Purba (Universitas Prima Indonesia)



Article Info

Publish Date
31 May 2026

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.

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Journal Info

Abbrev

algoritma

Publisher

Subject

Computer Science & IT

Description

Jurnal Algoritma merupakan jurnal yang digunakan untuk mempublikasikan hasil penelitian dalam bidang Teknologi Informasi (TI), Sistem Informasi (SI), dan Rekayasa Perangkat Lunak (RPL), Multimedia (MM), dan Ilmu Komputer (Computer ...