User Experience of Mobile Banking Application in Indonesia: New Technology of Banking

Purpose: This research delves into the user experiences associated with ten mobile banking applications in Indonesia. The study aims to highlight the technological innovations that drive user satisfaction, pinpoint areas requiring enhancement, and offer foresight into the evolving landscape of mobile banking in the region. Design/methodology/approach: Utilizing the KH-coder software, the data underwent rigorous quantitative text mining. Techniques such as frequency analysis, co-occurrence network analysis, and topic modeling were employed to discern pivotal themes within mobile banking applications. Further, statistical analyses rooted in co-occurrence words were conducted. Findings: The study scrutinized 5,720 online reviews, highlighting the pivotal role of online feedback in influencing consumer behavior, from product choices to app installations. The overall average rating was 3.76 out of 5, indicating a moderate level of user satisfaction. Reviews often raised concerns, with terms such as 'bug,' 'slow,' 'issue,' and 'problem' being prevalent. Conversely, reviews with a positive tone frequently included words like 'transfer,' 'previous,' 'number,' 'easy,' 'friendly,' 'user,' and 'feature,' suggesting greater user satisfaction. Through statistical analysis, ten distinct factors were identified, encompassing 26 words derived from co-occurrence patterns. Research limitations/implications: The study is geographically centered on Indonesia, potentially limiting its applicability to other regions. Relying on user reviews may not encompass the entirety of user experiences, given the potential bias towards extreme sentiments. The findings highlight the importance of technological advancements and user feedback in mobile banking's future, urging stakeholders to address areas of concern identified by users to enhance satisfaction and engagement. Originality/value: By harnessing a multi-dimensional analytical paradigm, encompassing term frequency, co-occurrence analysis, Latent Dirichlet Allocation (LDA), Exploratory Factor Analysis, and regression analysis, this study crafts a holistic blueprint for enhancing digital banking experiences, offering invaluable insights for stakeholders in the mobile banking domain.