What type of study is this?

This is a Sentiment Analysis study (also classified as: Support Vector Machine, User Review Analysis).

September 10, 2025

Assessment of mobile payment service based on user review in Indonesia

Key Points

User satisfaction with mobile payment services is assessed using sentiment analysis of reviews from Twitter, highlighting areas for improvement.
DANA achieved an accuracy of 83.83% and LinkAja 82.58% using the Support Vector Machine algorithm for user review analysis.
The analysis identified significant negative sentiment surrounding both mobile payment applications, with specific issues noted in customer service.
Improving responsiveness and reliability in customer service is crucial for enhancing user satisfaction and fostering loyalty in mobile payment services.

Abstract

This study evaluates user satisfaction with mobile payment services, focusing on sentiment of user reviews from Twitter. Four key dimensions—reliability, economic benefits, assurance, and responsiveness—were analyzed for two applications, DANA and LinkAja. This study used Support Vector Machine algorithm with an accuracy measurement using the Confusion Matrix reaching 83.83% for DANA and 82,58% for LinkAja. The ROC curve showed the best AUC result of 0.909 for DANA and 0.900 for LinkAja (Excellent Classification). Sentiment analysis revealed that both applications faced predominantly negative sentiment, except for the economic benefit dimension of LinkAja, which showed a higher proportion of positive sentiment. Major issues identified include slow problem resolution, unresponsive customer service, and occasional application errors. These challenges highlight user dissatisfaction and the need for improved customer service and system reliability. The findings underscore the importance of addressing user complaints promptly to enhance satisfaction and foster loyalty.

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