Aspect-Based Sentiment Analysis of Jkn Mobile Application Reviews Using the Random Forest Method and Information Gain as Feature Selection

Abstract

In the rapidly advancing digital age, applications have become integral to daily life. This study focuses on aspect-based sentiment analysis of reviews for the Mobile JKN application using the Random Forest and Information Gain methods. This technological approach is vital for understanding user opinions, guiding further improvements and developments. Google Play Store review data is employed, with rating scores serving as guides for sentiment classification. The study aims to provide in-depth insights into sentiments and aspects influencing Mobile JKN application reviews. Through this approach, the quality of healthcare services delivered via the application is anticipated to be continually enhanced.