Sentiment Analysis of Reviews Grab Application on Google Playstore Based on Methods Naïve Bayes

Authors

  • Alvian Nugroho Universitas Raharja
  • Nisa Febriyani Universitas Raharja
  • Heri Kurniawan Universitas Raharja

DOI:

https://doi.org/10.22441/collabits.v2i3.30263

Abstract

This research aims to conduct sentiment analysis of user reviews for the Grab application in the Google Play Store using the Naïve Bayes method. The research uses data in Indonesian language and analyzes sentiment in three classes: positive, neutral, and negative. The Naïve Bayes method is used to classify user reviews into the appropriate sentiment categories. The research utilizes the Google Play Store API and the Google_play_scrapper library to collect user review data. A total of 1195 reviews were successfully collected. The results of the sentiment analysis are expected to provide valuable insights for Grab in improving user experience and the quality of their application services.

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References

APJII. (2018). DAFTAR ISI B. PERILAKU PENGGUNA INTERNET INDONESIA.

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E. F. S. (2019). Sentiment Analysis Of Traveloka App Using Naïve Bayes Classifier Method. INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY

Primajaya, A., & Sari, B. N. (2018). Random Forest Algorithm for Prediction of Precipitation. Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM), 1(1), 27–31.

Romzi, M., & Kurniawan, B. (2020). PEMBELAJARAN PEMROGRAMAN PYTHON DENGAN PENDEKATAN LOGIKA ALGORITMA (Issue 2).

Julianto, Y., & Setiabudi, D. (2022). Analisis Sentimen Ulasan Restoran Menggunakan Metode Support Vector Machine.

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Published

2026-01-30

How to Cite

[1]
A. Nugroho, N. Febriyani, and H. Kurniawan, “Sentiment Analysis of Reviews Grab Application on Google Playstore Based on Methods Naïve Bayes”, Collabits, vol. 2, no. 3, pp. 151–153, Jan. 2026.

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