<![CDATA[This research aims to identify purchasing patterns of beverage products at a Beverage Franchise inJombang by applying the apriori algorithm, which the algorithm is one of the data mining methods used touncover association rules among a set of items. There are two important parameters used in findingassociation rules, namely support and confidence. This research utilizes sales transaction data of beverageproducts over February 2024. The analysis process includes several key stages, such as data collection,data preprocessing, parameter determination, application of apriori algorithm, and result analysis. Theresearch results show that apriori algorithm is capable to identifying the purchase patterns of beverageproducts conducted by consumers. Out of the 124 association rules formed, there are several itemcombinations with the strongest association rules among others. In the 3-itemset combination, there is acombination of purchasing Esteh Melati, Cookies & Cream, and Esteh Matcha Original with a confidencevalue of 100% and a lift ratio of 1,38. Meanwhile, in the 2-itemset combination, there is a combination ofpurchasing Esteh Matcha Original and Cookies & Cream with a confidence value of 90,48% and a liftratio of 1,25. Therefore, it can be concluded that apriori algorithm can understand consumers purchasingbehavior and assist business owners in making decisions to formulate strategies of their business.Keywords: Apriori Algorithm, Purchase Patterns, Beverage Products, Data Mining]]>
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