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Anzelia Anzelia
Penda Sudarto Hasugian

Abstract

Data mining is a search and analysis on a very large database so that an interesting pattern is found with the aim of extracting information and knowledge that is accurate and potential, as well as understandable and useful from a large database. In this final project, one of the data mining techniques is implemented, namely the a priori algorithmcan define the rule pattern of the data set. The data in this study aims to determine the pattern of sales at 212 mart supermarkets in Lubuk Pakam. This research is obtained from the results of transaction data in the form of consumer purchase receipts, the data used are 10 transaction data with 43 total products. From the results of manual calculations, there are 23 rule association results in accordance with the minimum limit values ​​for support and confidence that have been determined and the highest analysis results are found in french fries and chitato with a minimum support of 30% and 100% confidence. The results of the data mining process obtained can be used for the arrangement or arrangement of layout patterns that are adjusted to the association rules to suit consumer purchasing patterns.

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How to Cite
Anzelia, A., & Hasugian, P. S. (2020). Application of Data Mining in Determining Sales Patterns at 212 Mart Supermarkets in Lubuk Pakam Using the Apriori Algorithm. Journal of Intelligent Decision Support System (IDSS), 3(4), 10-17. Retrieved from https://idss.iocspublisher.org/index.php/jidss/article/view/17
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