<![CDATA[PT. Inka Raya has sales transaction data that can be processed to identify association patterns between products. The transaction data, which was previously used mainly as sales records, has not specifically provided information about products that frequently appear together in the same transaction. This study aims to apply data mining using the Apriori Algorithm to analyze sales patterns and to develop a web-based system that presents association rule results. The data used in this study consists of 510 sales transactions from PT. Inka Raya during the period of November to December 2025. The research stages include data selection, preprocessing, binary tabulation, itemset formation, support and confidence calculation, and association rule generation. The system was developed using PHP, CodeIgniter, Bootstrap, and MySQL, and was tested using Black Box Testing and White Box Testing methods. Based on data processing using a minimum support value of 10% and a minimum confidence value of 60%, 12 products met the 1-itemset criteria, 5 product combinations met the 2-itemset criteria, and 8 association rules met the minimum confidence value. The resulting association rules show product relationships that can be used as consideration by PT. Inka Raya in reading sales patterns and supporting purchase and product placement decisions.]]>
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