This study aims to implement a data mining application to produce association rules between items in a transaction to purchase goods of various types of goods simultaneously by determining support of 40% and confidence of 50%. Thus, if there is a consumer buying a type of goods. The problem that arises in the K92-Mart minimarket is that there are often no sales of goods that consumers want or are out of stock because they do not pay attention to stock. To overcome this problem, a data mining application was created using the Apriori Algorithm. By implementing this apriori algorithm, it is hoped that it can produce a decision from sales data that aims to determine the pattern of purchasing goods that are often purchased by consumers and are strategic in sales.