Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Locus Penelitian dan Pengabdian The Indonesian Journal of Computer Science
Mubina, Basma Fathan
Unknown Affiliation
Aerospace Engineering Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
User Review Analysis of the BNI Wondr Mobile Banking Application: Systematic Literature Review Mubina, Basma Fathan; Halim, Dicky; Budi, Indra; Ramadiah, Amanah; Putra, Prabu Kresna; santoso, Aris budi
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 8 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i8.4541

Abstract

In the digital age, mobile banking has become essential for facilitating efficient financial transactions, with the Wondr mobile banking application from Bank Negara Indonesia (BNI) emerging as a significant innovation in this sector. Designed to provide a secure and user-friendly experience, Wondr aims to meet the diverse needs of its customers. However, to enhance its service and ensure user satisfaction, BNI must actively engage with customer feedback. This study leverages user reviews from platforms like Google Play Store to gain insights into the strengths and weaknesses of the Wondr application. Employing text analysis techniques, we utilise topic modeling through Latent Dirichlet Allocation (LDA) to extract relevant themes from these reviews to identify key areas for improvement and generate targeted recommendations. The findings of this research are intended to inform the ongoing development of the Wondr application, ultimately enhancing user experience and reinforcing BNI’s position within the digital banking landscape.
Comparative Topic Modelling of Mobile Banking User Reviews Using LDA and BERTopic: A Case Study of wondr by BNI Halim, Dicky; Budi, Indra; Mubina, Basma Fathan; Budi Santoso, Aris; Kresna Putra, Prabu
The Indonesian Journal of Computer Science Vol. 15 No. 2 (2026): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v15i2.5118

Abstract

This study explores user reviews of the Wondr mobile banking application to identify factors that influence user experience and service quality. The dataset, obtained from the Google Play Store, was processed through several preprocessing steps, including normalization, stopword removal, and stemming. Two topic modelling methods were applied: Latent Dirichlet Allocation (LDA) as a probabilistic baseline and BERTopic as an embedding-based approach. The LDA model was evaluated using coherence scores to determine the most suitable number of topics, while BERTopic was assessed based on topic distribution, interpretability, and additional coherence analysis. The results show that BERTopic produces more semantically meaningful and contextually rich topics, particularly in capturing short-text user reviews. Although BERTopic achieves lower overall coherence compared to LDA, certain topics demonstrate high semantic consistency, especially for well-defined issues such as login verification problems. The analysis reveals that most user feedback is concentrated on positive user experience, while critical issues related to login verification and system errors remain significant concerns. These findings provide actionable insights for improving mobile banking services and demonstrate the effectiveness of embedding-based topic modeling in financial text analytics. These findings highlight a trade-off between statistical consistency and semantic richness in topic modeling approaches. The results provide actionable insights for improving mobile banking services and demonstrate the effectiveness of combining probabilistic and embedding-based methods in financial text analytics.
Co-Authors Budi Santoso, Aris Budi, Indra Halim, Dicky Kresna Putra, Prabu Prabu Kresna Putra, Prabu Kresna Ramadiah, Amanah Santoso, Aris Budi