Abstract
Musyawarah store is a grocery store that provides a variety of daily needs. The products sold at the deliberative shop include necessities, kitchen spices, toiletries, laundry soap, and house cleaners. So far, sales data has never been analyzed. Data analysis with data mining can generate new knowledge to help shop owners manage inventory strategies and display items for sale. This study aimed to determine the pattern of the high frequency of items sold in the Musyawarah grocery store using data mining methods. The Apriori algorithm analyzes sales transactions at the Musyawarah grocery store. Based on the observations and calculations that the authors have made of the final association results, namely, if you buy eggs, you will buy Indomie rebus with 50% support and 58% confidence, and if you buy Indomie rebus, you will buy eggs with 50% support and 100% confidence. While sasa is the product that does not sell well with the smallest confidence value.
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