This research aims to analyze purchasing patterns in Komol Kopi transaction data using the Apriori algorithm. This algorithm enables the discovery of relationships between items in large datasets that can be used to support business decisions, such as bundling promotions and inventory management. The dataset includes 12 transactions with various combinations of items, such as Kopi Hitam, Kopi Tubruk, and Nasi Telur. The analysis results show some significant purchase patterns with high support, confidence, and lift values. An example of an association found is between Kopi Hitam and Es Teh, which provides insights for more effective marketing strategies. This study confirms that the Apriori algorithm is an efficient tool in unearthing purchasing patterns, providing a solid foundation for the development of data-driven business strategies. Further research can integrate this analysis with recommendation systems to improve customer experience.
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