PENERAPAN ALGORITMA APRIORI PADA DATA TRANSAKSI PENJUALAN DI TOKO BERKAH BERLIMPAH

Abstract

The aim of this research is to determine sales transaction trends at the Berkah Abundant Store using the Apriori algorithm. One technique for identifying relationships between items in a transaction dataset is the Apriori algorithm. Toko Berkah Abundant provides sales transaction data used in this research. Preparing data for research involves applying the Apriori algorithm, analyzing the data, and interpreting the findings. Relevant transaction patterns between products purchased by customers simultaneously are displayed in the analysis results. Abundant Blessings Store management can use this information to make better judgments regarding product placement, sales tactics, and promotions. Utilization of the Apriori algorithm on sales transaction data at the Berkah Abundant store produces in-depth information about consumer purchasing habits which can be applied to increase operational effectiveness and store revenue. Products A and E are most often purchased together by customers, according to the a priori algorithm calculation procedure. So it can be concluded that products A and E have a support value of 61% and 53% respectively. Based on a priori calculations, if a customer buys product A, at least 30% of the time they will buy product E. Products that sell well can be identified based on a priori calculations of association rules, so that Toko Berkah Abundant can create product packaging that contains derivative products from product combinations in an effort to increase sale.