Importance Performance Analysis (IPA) of Google Reviews Sentiments Based on SERVQUAL Dimension for Public Health Center Service in Surabaya

Abstract

Google Reviews can serve as a digital mirror to gauge how the public evaluates the services of community health centers. This study focuses on analyzing the sentiment of Google Reviews for community health centers in Surabaya, mapping reviews into the SERVQUAL dimensions using Gap Analysis and Importance–Performance Analysis (IPA), and identifying the most influential keywords via TF-IDF within a GUI system. This study applies the Knowledge Discovery in Databases (KDD) workflow. Data was obtained by scraping reviews from 63 community health centers in Surabaya. Subsequently, sentiment was determined based on user ratings, then classified into the five SERVQUAL dimensions, and analyzed using the GAP analysis and Importance-Performance Analysis (IPA). The results indicate that positive public perceptions predominate. However, all dimensions still show negative scores, suggesting that service quality has not yet fully met user expectations. In the IPA analysis, Responsiveness, Assurance, and Empathy are categorized in Quadrant II as aspects that require maintenance, while Tangibles and Reliability fall into Quadrant III as low-priority aspects. Notably, no dimension is in Quadrant I. Additionally, TF-IDF successfully captures keywords such as “queue,” “long,” “friendly,” “clean,” and “procedure,” and has been successfully implemented in the GUI for automatic classification. Building on these results, this study confirms that digital reviews combined with sentiment analysis, SERVQUAL, and Importance-Performance Analysis (IPA) can serve as a more objective, practical, and sustainable evaluation tool for Public health center services.