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This study aims to analyze consumer purchasing patterns at Ryo Jaya Buah Stores using a priori algorithm. A priori algorithm is one of the data mining methods used to find relationships between items in a large dataset through the process of association. This research was conducted by collecting sales transaction data in a certain period at the Ryo Jaya Buah Shop. The data obtained is then processed and analyzed using software that supports the implementation of the Apriori algorithm. The results of this study show a significant variety of purchasing patterns among the products sold in the store. By knowing these patterns, Toko Ryo Jaya Buah can optimize product structuring, marketing strategies, and promotional offers to increase sales. In addition, testing a total of 173 transactions with a support value of 0.02 and a confidence value of 0.01 resulted in a number of rules that can be used as useful new information. After comparing the test results with and without Rapidminer 10.0 software, it is clear that the results of manual calculations are not significantly different from the results of Rapidminer 10.0 software.
Ricardo et al. (Mon,) studied this question.