Analysis of Transaction Patterns and User Preferences in the DANA Application Using the Apriori Algorithm for Digital Wallet Service Optimization
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Abstract
DANA emerges as a practical solution for conducting fast, efficient, and secure financial transactions. However, its rapid growth presents a new challenge for developers: understanding user transaction patterns and behavior in depth. Each user has different preferences and habits; some regularly use the bill payment feature, others more frequently perform top-ups and purchase mobile credit, while some utilize the balance transfer feature. Data processing results reveal that the combination of Top-Up and Electricity Bill payments has a support value of 60% and a confidence of 85.7%. In contrast, the combination of Electricity Bill Payment ke Top-Up shows the highest confidence value of 100%. This indicates that almost all users who pay electricity bills will always top up their balance before transacting. Analyzing these transaction patterns is crucial as it provides valuable insights for developers to optimize features, enhance service personalization, and design user behavior-based promotional strategies.
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