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Journal : The Indonesian Journal of Computer Science

Measuring mobile banking service quality using Topic Modeling and Term Ranking: A case study of an Indonesian digital bank Anggraini, Veny; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4517

Abstract

The rapid expansion of digital transactions in Indonesia is driving the transformation of both traditional and digital banks. Since digital banks operate without physical branches, all banking services are via mobile banking apps. This study examines mobile banking service quality using text mining techniques like topic modeling and term ranking to analyze 11,815 user reviews from app stores and assess customer satisfaction through ratings. The research involves extracting and preprocessing reviews, identifying key topics, and linking them to satisfaction levels. Seven service dimensions were found: customers were satisfied with Enjoyment, Debit Card Delivery, and Feature-Free Transactions but dissatisfied with Accessibility, Data Privacy, Loan Services, and Touchless Customer Support. Debit Card Delivery and Feature-Free Transactions were highlighted as significant factors in Indonesia's digital banking market. With limitations in analyzing user reviews in Bahasa Indonesia, the findings are specific to the Indonesian digital banking context and may not be applicable elsewhere.
Uncovering the Reasons Behind Abstain Voters' Stances in the 2024 Indonesian Presidential Election: Social Media X Study Cases Putri, Irzanes; Insani, Faiz Nur Fitrah; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4126

Abstract

The Indonesian Government expects the participation of all Indonesian people in holding General Elections. However, according to the 2019 Political Statistics by BPS, there were 34.75 million people who did not exercise their right to vote or were abstain voters (golput) in the 2019 Election. This research aims to analyze individual attitudes towards abstaining voters using stance analysis and topic modelling. From 9,045 collected tweets, subsequent manual annotation revealed 2,566 pro stances, 5,264 neutral stances, and 1,215 contra stances. The classification models utilized are Random Forest, Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Gradient Boosting. The classification outcomes will be analyzed by comparing the accuracy, precision, recall, and F1-score results based on their algorithms and n-grams. The results obtained from the stance analysis show that Random Forest achieved the highest accuracy and precision scores, with values of 84% and 83%, respectively. The discussion topic among those supporting golput due to low trust in the presidential and vice-presidential candidates. Other topics mentioned public feels dissatisfied with the pairs of candidates.