Sentiment Analysis of JMO Application Reviews on the Google Play Store Using BERT - Hendi Putra Wijaya; Adhityah Anugrah; Mira Afrina; Ali Ibrahim (STMIK Indonesia Banda Aceh, 2026)
The development of digital technology has encouraged increased use of online-based public service applications, including the JMO (Jamsostek Mobile) application developed by BPJS Ketenagakerjaan to provide easy access for its participants. This application has received many user reviews on the Google Play Store, reflecting the level of satisfaction and public perception of service quality. However, the large and unstructured volume of comments makes manual analysis difficult. This study aims to conduct sentiment analysis on user comments about the JMO application on the Play Store using the Bidirectional Encoder Representations from Transformers (BERT) model. The research method involves collecting comments through web scraping, text preprocessing (such as data cleaning, normalization, and tokenization), and sentiment labeling (positive, negative, and neutral). Evaluation using precision, recall, and F1-score is employed to describe the results. The study is expected to identify patterns of user sentiment and public perceptions of the JMO application. It is also expected to serve as an evaluation material and input for developers to improve service quality and user experience.