• Abstract

    Islamic banking in Indonesia has experienced significant growth since its introduction in the early 1990s, with digital transformation becoming a critical driver of financial inclusion and service accessibility. The establishment of Bank Syariah Indonesia (BSI) in 2021, formed through the merger of several state-owned Islamic banks, marked a pivotal moment in the sector's development. BSI Mobile, as the bank's primary digital platform, serves as a crucial interface for delivering Sharia-compliant financial services to millions of users. However, despite rapid technological advancement, questions remain regarding user satisfaction, trust, and the effectiveness of digital Islamic banking services. This study explores public sentiment toward BSI Mobile by analyzing 25,592 user reviews collected from the Google Play Store using Natural Language Processing (NLP) and Machine Learning techniques. Sentiment classification was conducted based on Ekman's Six Basic Emotions framework, categorizing user feedback into Joy, Surprise, Fear, Sadness, Disgust, and Anger. Two supervised machine learning models—Naïve Bayes and Logistic Regression—were employed to classify reviews into four key aspects: App Performance, Security & Privacy, App Functionality, and User Interaction. Both models demonstrated high accuracy (89.7%) with equivalent performance metrics (AUC: 0.948, F1: 0.898). The findings reveal a highly polarized user experience, with 10,618 one-star ratings and 10,554 five-star ratings, indicating that users have either very positive or very negative experiences. While Joy (11,180 cases) and Surprise (9,943 cases) dominated positive sentiments, Fear (3,072 cases) emerged as a significant concern, primarily related to security and transaction reliability. App Performance and Security & Privacy were identified as the most critical factors influencing user satisfaction. The study provides actionable insights for improving digital Islamic banking services, emphasizing the need for enhanced system stability, robust security measures, and continuous feature optimization. These findings contribute to the broader understanding of digital transformation in Islamic finance and offer practical recommendations for banking institutions, policymakers, and FinTech developers to strengthen user trust and promote wider adoption of Sharia-compliant financial technology solutions.

  • References

    1. Adrutdin, K. F., Gadar, K., Rahim, N. S. A., & Hasim, M. (2020). CUSTOMER EDUCATION IN ISLAMIC BANKING IN MALAYSIA. Journal of Critical Reviews, 7(8). https://doi.org/10.31838/jcr.07.08.26
    2. Afif, M., & Samsuri, A. (2022). Integration of Fintech and Islamic Banking in Indonesia: Opportunities and Challenges. Cakrawala: Jurnal Studi Islam, 17(1). https://doi.org/10.31603/cakrawala.7051
    3. Alfani, D. S., Yuniarto, A., Handrito, R., Shabri, D., Alfani, A., M.S, R. P. Y., & Handrito. (2023). THE EFFECT OF PERCEIVED EASE OF USE ON INTENTION TO USE ON BANK SYARIAH INDONESIA MOBILE BANKING USERS IS MEDIATED BY E-TRUST AND RELIGIOSITY AS MODERATORS. International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS), 3(4). https://doi.org/10.54443/ijebas.v3i4.1024
    4. Amin, M., Isa, Z., & Fontaine, R. (2013). Islamic Banks: Contrasting the drivers of customer satisfaction, image, trust, and loyalty of Muslim and Non-Muslim customers in Malaysia. International Journal of Bank Marketing, Volume 31, 79–97.
    5. Aziz, M. A., Cahyo, E. N., & Labolo, S. N. S. D. (2022). The Overview of Sharia Principles on BSI Mobile Banking. Al-Iktisab: Journal of Islamic Economic Law, 6(2). https://doi.org/10.21111/al-iktisab.v6i2.8683
    6. Aziz, M. M., Purbalaksono, M. D., & Adiwijaya, A. (2023). Method comparison of Naïve Bayes, Logistic Regression, and SVM for Analyzing Movie Reviews. Building of Informatics, Technology and Science (BITS), 4(4). https://doi.org/10.47065/bits.v4i4.2644
    7. Bashir, I., & Madhavaiah, C. (2015). Consumer attitude and behavioural intention towards Internet banking adoption in India. Journal of Indian Business Research, 7(1), 67–102. https://doi.org/10.1108/JIBR-02-2014-0013
    8. Cambria, E., Schuller, B., Xia, Y., & Havasi, C. (2013). New Avenues in Opinion Mining and Sentiment Analysis. IEEE Intelligent Systems, 28(2), 15–21. https://doi.org/10.1109/MIS.2013.30
    9. Chen, W., Yan, X., Zhao, Z., Hong, H., Bui, D. T., & Pradhan, B. (2019). Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China). Bulletin of Engineering Geology and the Environment, 78(1), 247–266. https://doi.org/10.1007/s10064-018-1256-z
    10. Cherni, S., & Amar, A. B. (2024). Does digitalization affect shariah supervisory board efficiency? Evidence from Islamic banks. Journal of Islamic Accounting and Business Research, 14(3). https://doi.org/10.1108/jiabr-03-2023-0077
    11. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
    12. Dawood, H. M., Zadjali, D. F. A., Rawahi, M. A., Karim, D. S., & Hazik, D. M. (2022). Business trends & challenges in Islamic FinTech: A systematic literature review. F1000Research, 11. https://doi.org/10.12688/f1000research.109400.1
    13. Feng, H., & Shi, F. (2019). Deep Learning in Natural Language Processing. Natural Language Engineering, 27, 373–375. https://doi.org/10.1017/S1351324919000597
    14. Hakimi, F., Maf’ula, F., & Gultom, R. Z. (2024). Pre- and post-merger efficiency of Islamic state-owned bank: A case study of Bank Syariah Indonesia. Journal of Islamic Economics Lariba, 10(1). https://doi.org/10.20885/jielariba.vol10.iss1.art25
    15. Hamsin, M. K., Halim, A., Anggriawan, R., & Lutfiani, H. (2023). Sharia E-Wallet: The Issue of Sharia Compliance and Data Protection. Al-Manahij: Jurnal Kajian Hukum Islam, 17(1). https://doi.org/10.24090/mnh.v17i1.7633
    16. Hassan, M. K., Rabbani, M., & Ali, M. (2020). Challenges for the Islamic Finance and banking in post COVID era and the role of Fintech. Journal of Economic Cooperation and Development, 41, 93–116.
    17. Hilmi, A. F. (2021). OVERVIEW OF BSI DIGITALIZATION IN CREATING A HEALTHY COMPETITIVE MARKET BY OPTIMIZING EXISTING STATE-OWNED BANK CUSTOMERS. Airlangga International Journal of Islamic Economics and Finance, 17(2). https://doi.org/10.20473/aijief.v4i2.31403
    18. Iqbal, M., Sumantri, R., & Khoirunnisa, R. (2022). ACCELERATION OF FINANCIAL TECHNOLOGY GROWTH IN ISLAMIC BANKS AS AN EXISTENCE EFFORT TO FACE THE PANDEMIC OF COVID-19. Al-Masraf: Jurnal Lembaga Keuangan Dan Perbankan, 7(2). https://doi.org/10.15548/al-masraf.v7i2.251
    19. Irawan, H. (2023). The role of Islamic banks in developing a sharia-based economy in the digital era in Indonesia. Journal of Islamic Economics Lariba, 9(2). https://doi.org/10.20885/jielariba.vol9.iss2.art9
    20. Jasy, M. D. H., Hasan, S. A., Sagor, M. I. K., Noman, A. M., & Ji, J. (2021). A Performance Evaluation of Sentiment Classification Applying SVM, KNN, and Naive Bayes. 2021 International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA), (p. 56–60). Tirana, Albania. https://doi.org/10.1109/contesa52813.2021.9657115
    21. Juwita, R., Kusumah, A. D., Aqila, T. S., Tsabitah, H., & Syauqi, M. F. (2023). The Intention to Use Mobile Banking as a Financial Technology Service among Islamic Bank Users. The Indonesian Capital Market Review, 15(1). https://doi.org/10.21002/icmr.v15i1.1166
    22. Khan, H. U., Malik, M. Z., Nazir, S., & Khan, F. (2023). Utilizing Bio Metric System for Enhancing Cyber Security in Banking Sector: A Systematic Analysis. IEEE Access, 11, 80181–80198. https://doi.org/10.1109/ACCESS.2023.3298824
    23. Kholidah, N., Arifiyanto, M., Subowo, E., & Pambuko, Z. B. (2023). Factors Influencing the Interest in Using Sharia Digital Banking Applications in Indonesia. Cakrawala: Jurnal Studi Islam, 18(2). https://doi.org/10.31603/cakrawala.10294
    24. Kishnani, U., Noah, N., Das, S., & Dewri, R. (2022). Privacy and Security Evaluation of Mobile Payment Applications Through User-Generated Reviews. Proceedings of the 21st Workshop on Privacy in the Electronic Society, 159-173. https://doi.org/10.1145/3559613.3563196
    25. Laldin, M. A., & Furqani, H. (2019). Fintech and Islamic finance: Setting the Sharī‘ah parameters. In Umar A. Oseni & S. Nazim Ali (eds.), Fintech in Islamic Finance: Theory and Practice (pp. 7). Routledge. https://doi.org/10.4324/9781351025584
    26. Llazo, E., Ryspaeva, A., Kubiczek, J., Mehdiyev, V., & Ketners, K. (2024). Trends and Prospects of Financial System Development in the Context of Digitalization. Theoretical and Practical Research in Economic Fields, 15(4), 783. https://doi.org/10.14505/tpref.v15.4(32).01
    27. Lubis, F. A. (2024). User Sentiment Analysis Towards Islamic Banking Applications in Indonesia. Journal of Islamic Economic and Business Research, 4(1). https://doi.org/10.18196/jiebr.v4i1.342
    28. Milza, A. T., Fasa, M. I., Suharto, S., & Fachri, A. (2021). IMPLEMENTASI BSI MOBILE SEBAGAI WUJUD TERCAPAINYA PAPERLESS DAN PENERAPAN GREEN BANKING. IJAB Indonesian Journal of Accounting and Business, 3(1), 1–12. https://doi.org/10.33019/ijab.v3i1.3
    29. Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), 329–340. https://doi.org/10.1016/j.bir.2017.12.003
    30. Pamungkas, P., Pratiwi, D. I., & Bakkar, Y. (2023). The merger of Islamic banks and their impact on the stability of the country’s economy. Sebelas Maret Business Review, 7(2). https://doi.org/10.20961/smbr.v7i2.55845
    31. Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224–235. https://doi.org/10.1108/10662240410542652
    32. Raymond, M. I., Atta, A. A. B., Barrak, T. A., Lutfi, A., & Alrawad, M. (2024). Digital transformation: An empirical analysis of operational efficiency, customer experience, and competitive advantage in Jordanian Islamic banks. Uncertain Supply Chain Management, 12. https://doi.org/10.5267/j.uscm.2024.1.015
    33. Riyanto, S., Sitanggang, I. S., Djatna, T., & Atikah, T. D. (2023). Comparative Analysis using Various Performance Metrics in Imbalanced Data for Multi-class Text Classification. International Journal of Advanced Computer Science and Applications, 14(6). https://doi.org/10.14569/ijacsa.2023.01406116
    34. Rogers, R. W. (1975). A Protection Motivation Theory of Fear Appeals and Attitude Change1. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803
    35. Samudera, B. D., Nurdin, N., & Aidilof, H. A. K. (2024). Sentiment Analysis of User Reviews on BSI Mobile and Action Mobile Applications on the Google Play Store Using Multinomial Naive Bayes Algorithm. International Journal of Engineering, Science and Information Technology, 4(4). https://doi.org/10.52088/ijesty.v4i4.581
    36. Sari, A. P., Sukardi, B., & Abadi, M. K. R. (2024). ADOPTION OF USER SATISFACTION WITH THE UTAUT2 MODEL IN USING INDONESIA SHARIA MOBILE BANKING. FINANSIA : Jurnal Akuntansi Dan Perbankan Syariah, 7(1). https://doi.org/10.32332/finansia.v7i1.8165
    37. Sari, M. P. (2022). The Evaluation of Mergers on the Financial Performance of PT Bank Syariah Indonesia. At-Taqaddum, 4(1). https://doi.org/10.21580/at.v14i2.17908
    38. Schiebler, T., Lee, N., & Brodbeck, F. (2025). Expectancy-disconfirmation and consumer satisfaction: A meta-analysis. Journal of the Academy of Marketing Science, 57. https://doi.org/10.1007/s11747-024-01078-x
    39. Setiawan, J., Milenia, A., & Faza, A. (2023). An Integrated Approach for Sentiment Analysis and Topic Modeling of a Digital Bank in Indonesia using Naïve Bayes and Latent Dirichlet Allocation Algorithms on Social Media Data. 2023 4th International Conference on Big Data Analytics and Practices (IBDAP), 1–7. https://doi.org/10.1109/IBDAP58581.2023.10271956
    40. Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review. Telematics and Informatics, 32(1), 129–142. https://doi.org/10.1016/j.tele.2014.05.003
    41. Sitorus, Z., Saputra, M., Sofyan, S. N., & Susilawati. (2024). SENTIMENT ANALYSIS OF INDONESIAN COMMUNITY TOWARDS ELECTRIC MOTORCYCLES ON TWITTER USING ORANGE DATA MINING. INFOTECH Journal, 10(1). https://doi.org/10.31949/infotech.v10i1.9374
    42. Suhartanto, D., Dean, D., Ismail, T., & Sundari, R. (2019). Mobile banking adoption in Islamic banks. Journal of Islamic Marketing, 11(6). https://doi.org/10.1108/jima-05-2019-0096
    43. Tripalupi, R. I., Yulianti, L., & Naafisah, D. D. (2021). Optimization of Financial Technology as an Opportunity for Development of Islamic Microfinance Institutions. International Journal of Artificial Intelligence Research, 6(1). https://doi.org/10.29099/ijair.v6i1.340
    44. Yudhistira, Y., & Talita, A. S. (2024). Analyzing Public Sentiment Towards BSI Service Disruptions Through X: Naïve Bayes Algorithm. Sinkron, 8(3). https://doi.org/10.33395/sinkron.v8i3.13729
    45. Zahiroh, M. Y. (2020). Cybersecurity Awareness and Digital Skills on Readiness For Change in Digital Banking. Li Falah: Jurnal Studi Ekonomi Dan Bisnis Islam, 5(2). https://doi.org/10.31332/lifalah.v5i2.2271
    46. Zeithaml, V., Parasuraman, A. P., & Malhotra, A. (2002). Service Quality Delivery Through Web Sites: A Critical Review of Extant Knowledge. Journal of the Academy of Marketing Science, 30, 362–375. https://doi.org/10.1177/009207002236911
    47. Zouari, G., & Abdelhedi, M. (2021). Customer satisfaction in the digital era: Evidence from Islamic banking. Journal of Innovation and Entrepreneurship, 10. https://doi.org/10.1186/s13731-021-00151-x

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Copyright (c) 2025 The Authors

How to cite

Rumra, A., Sandy, T. A., Sarif, A., Wibawa, K. D., Darman, Alwi, A. C., & Septianto, T. (2025). Exploring public sentiment toward Islamic banking apps: A case study of BSI mobile in Indonesia. Multidisciplinary Science Journal, 8(6), 2026385. https://doi.org/10.31893/multiscience.2026385
  • Article viewed - 818
  • PDF downloaded - 368