<![CDATA[In an era of increasingly intense business competition, entrepreneurs in the healthcare sector, such as pharmacies, are required to optimize the use of transaction data. Apotek Permata Sejahtera has experienced a daily increase in sales transaction volume, resulting in an accumulation of data without further analysis. Therefore, a method is needed to identify associations between pharmaceutical products that are frequently purchased together by customers to support sales strategies and product arrangement. This study applies the Hash-Based algorithm to discover association patterns from drug sales transaction data between February and September 2024. The research stages include tabular data construction, determination of minimum support, hash address computation, calculation of minimum confidence, confidence evaluation, and formulation of association rules. The results show that the maximum itemset combination meeting the minimum support threshold of 40% reaches only up to the 5-itemset level, with a single final combination. From the 41 combinations that met the support criteria, 37 rules were identified with a minimum confidence of 80%, indicating strong relationships among pharmaceutical products. These findings offer practical contributions to sales strategy planning, inventory management, and product layout optimization in pharmacies to enhance operational efficiency and customer satisfaction]]>
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