<![CDATA[This study aims to identify consumer purchasing patterns for food and beverage products using the Apriori algorithm. The main issue addressed is inefficiency in stock management, necessitating a data-driven approach to enhance business effectiveness. The research was conducted at Kedai Dhino Thai Tea by analyzing 1.5 years of transaction data. The methodology includes data collection, data cleaning, and the application of the Apriori algorithm to uncover associations between frequently purchased products. The analysis results reveal that certain product combinations have strong associations, such as Mie Yamin Asin and Lumpia with 77% confidence, and Ocha and Black Sun with 71% confidence. This information can assist business owners in optimizing inventory management, formulating more effective marketing strategies, and designing more attractive promotional packages. Thus, the Apriori algorithm proves to be a valuable tool in supporting data-driven decision-making in the food and beverage industry, improving efficiency and profitability. Keywords— Apriori algorithm, data mining, market basket analysis, purchasing patterns, marketing strategy. ]]>
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