The second home coffee shop was established in November 2020. Based on interviews with the owner, sales transactions increased from March to July 2021 by approximately 35%. As a result, the supply of beverage ingredients is not controlled, so the owner has difficulty choosing the ingredients to be purchased the following month. Determination of the purchase of beverage ingredients purchased simultaneously can be done using association rules. The application of data mining methods can be used to overcome these problems. There are several concepts and techniques used in the data mining process, one of which is the association technique. In this study, the formation of association rules using the Apriori Algorithm. This study applies the Apriori Algorithm with a minimum support value of 30%-100% while a minimum confidence value of 60%-100%. From the results of the discussion and data analysis, it can be seen that the Apriori Algorithm is able to produce the rules needed by the owner. In this study, the best support and confidence values were 78% and 80% because they produced 30 (thirty) association rules containing 5 (five) itemsets. Meanwhile, the support value of 98% and the confidence value of 100% only resulted in 4 (four) rules containing only 2 (two) item sets. This is not recommended for the owner, because it can incur logistics costs.

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