Assessment of mobile payment service based on user review in Indonesia

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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Publication Details

Journal
Communications in Humanities and Social Sciences
Published
2024-12-31
DOI
https://doi.org/10.21924/chss.4.2.2024.81
Primary Topic
SMEs Development and Digital Marketing
Type
article
Field-Weighted Citation Impact
0.00
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article

Assessment of mobile payment service based on user review in Indonesia

Rahmat Nurcahyo, Intan Novita Dewi, Farizal Farizal
Communications in Humanities and Social Sciences
SMEs Development and Digital Marketing
article

Assessment of mobile payment service based on user review in Indonesia

Rahmat Nurcahyo, Intan Novita Dewi, Farizal Farizal
article en

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.

Communications in Humanities and Social SciencesVol. 4(2)
University of Indonesia (ID), Universitas Pembangunan Nasional Veteran Jakarta (ID)
Openalex Percentile: Top 39%
SMEs Development and Digital Marketing
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