<![CDATA[This study aims to identify consumer purchasing patterns at Bintang Waitabula Mobile Store using data mining techniques, specifically the FP-Growth algorithm. Transactional data were collected through documentation and processed using RapidMiner version 10.1. The FP-Growth method was selected for its efficiency in discovering frequent item combinations without generating candidate sets, unlike the Apriori algorithm. The analysis yielded two association rules with confidence values above 60%, indicating a strong relationship between commonly purchased mobile phone brands such as Samsung and Vivo. The process and results were visualized using diagrams and rule descriptions to support easier interpretation. These findings can serve as the foundation for decision-making in marketing strategies and inventory management. The FP-Growth implementation proved to be efficient and suitable for small to medium-sized retail enterprises.]]>
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