PENERAPAN ALGORITMA APRIORI UNTUK MENEMUKAN ATURAN ASOSIASI DALAM TRANSAKSI BELANJA KONSUMEN PADA MINIMARKET (STUDI KASUS: REZEKI GEMILANG JL. GANET KM.11 TANJUNGPINANG)

Abstract

Data mining in the business sector is needed because the inventory system in a minimarket is a top priority that must be stocked in anticipation of empty goods, so that business owners can find out what items are selling best and the minimum stock of an item. This condition can affect customer service and minimarket income. Therefore, this program was created by utilizing sales transaction data every day, in order to assist the minimarket in obtaining useful information using data mining techniques. In this study, the data analyzed is the data of consumer shopping transactions at Rezeki Gemilang minimarket, Tanjungpinang City for 4 months as many as 7312 transactions to find association rules using a priori algorithm. The test was carried out using a minimum support of 0.01 and a minimum confidence of 0.25. The results showed that if you buy France, the consumer will buy cigarettes has the highest confidence value, namely 0.8184, Support 0.02339 explains that all analyzed transactions show that French and cigarettes are purchased simultaneously, the lift is 3.46914 which shows the validity of the association, the conviction is 4.20754 and the leverage is 0.01665.