Track: Business Management

Abstract

Understanding consumer buying behavior is compulsory in business. By understanding the purchasing behavior, a supermarket can effectively make decisions regarding many things, such as the placement of goods or carry out appropriate promotional activities. One of affected the consumer purchasing pattern is budget, the amount of the budget is undoubtedly related to the income of the consumer. This study aims to reveal changes in consumer purchasing patterns in three periods in one month, namely the first ten days in a month, the second 10 days, and the last ten days in a month. Thus, to answer these objectives, data mining is used with the Association Rules technique. The CRISP-DM method is used as a guide in the steps towards the data mining process. The results indicate that consumer purchase patterns are different in all three periods in one month. In the first ten days of the month, the association between instant noodles and chicken eggs is quite complicated. In the second 10 days, a new association appeared, namely cooking oil and broiler chicken, and on the third day, only one association rule appeared. This study also provides a snapshot of another possibility related to the use of association rules.