Application of Associations Using the Apriori Algorithm to Analyze Consumer Purchase Patterns at Grocery Stores
DOI:
https://doi.org/10.55123/jomlai.v1i4.1679Keywords:
Apriori, Association, Data Mining, Consumer, Purchase PatternAbstract
The grocery store sells various types of ingredients for everyday life. Every day many customers shop at the grocery store. Every item sold at the Grocery Store will generate sales data, but this data cannot be utilized optimally. So we need a data analysis to help the Grocery Store gain knowledge of sales patterns in a certain period. The algorithm used as the primary process of analyzing the sale of ingredients in grocery stores is an a priori algorithm using the application of a minimum support value of 50% and a minimum confidence value of 70%, which meets the minimum support value and minimum confidence value, and sales transactions to find association rules. The Apriori algorithm test results will show results that have met the needs and determine the pattern of purchasing materials at the Grocery Store based on the items that customers most frequently purchase.
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