ANALYSING SERVICE QUALITY USING SENTIMENT ANALYSIS AND TOPIC MODELING: A CASE STUDY OF THE LIVIN MANDIRI APPLICATION

With the increasing number of m-banking users, understanding customer satisfaction has become crucial for banks in improving service quality and maintaining loyalty. This study aims to evaluate the satisfaction level regarding the service quality of the Livin Mandiri m-banking application using sentiment analysis and topic modeling. The data were gathered from 13,692 user reviews on the Google Play Store through web scraping techniques. After data cleansing and processing, sentiment analysis was conducted to identify trends in positive, negative, and neutral sentiments. Topic modeling using the Latent Semantic Indexing (LSI) method was employed to gain deeper insights into user discussions about service quality. The findings reveal that, although the Livin Mandiri application offers various useful features, the majority of user reviews are negative. Topic modeling further highlights that the primary complaints focus on technical issues such as transaction failures and verification challenges. Additionally, the study indicates a need to enhance application stability and customer service to improve user satisfaction. This study makes a significant contribution to understanding the service quality of m-banking applications by combining sentiment analysis and topic modeling, offering valuable insights for the future development and improvement of applications in the banking sector.