Penerapan Data Mining Untuk Analisis Pola Pembelian Pelanggan Menggunakan Algoritma Apriori (Studi Kasus: Toko Jihan) - Handala Simetris Harahap; Ratna Arista (Prosiding Sains dan Teknologi, 2024)
Determining item combinations and item layout based on consumer purchasing tendencies is one of the solutions for Jihan Stores in developing marketing strategies so as to increase sales at the store. The algorithm that can be used to find any combination of items that are often purchased together at a time is the Apriori Algorithm, this Apriori Algorithm includes the type of rules in data mining, namely to determine associative rules between a combination of items, the results of associative rules from consumer purchasing analysis Thus, the shop owner can adjust the placement of his goods or design a marketing campaign by giving a discount on the combination of these items. Based on sales transaction data within 3 months and processed using WEKA at Jihan Stores, an analysis is carried out using an a priori algorithm with a minimum support parameter of 50% and a minimum confidence of 80%. The results of data processing with WEKA that meet the support value and the highest confidence value are that if you buy noodles, then you are likely to buy eggs.