PENERAPAN ALGORITMA APRIORI TERHADAP POLA PEMBELIAN KONSUMEN UNTUK MENENTUKAN JUMLAH PERSEDIAAN BARANG

Abstract

The business field is one of the businesses that has a lot of data, one of which is sales transaction data. Sales transaction data can be used as an effort to improve business quality to maximize profits, so we need a system that can provide information in regulating the availability of goods so that it will minimize losses. This study aims to determine consumer purchasing patterns so that it is known what goods are most often purchased by consumers so that they can determine the amount of inventory. There are two methods used in this study, namely the Apriori Algorithm which is used to determine consumer purchasing patterns using sales transaction data and the Economic Order Quantity (EOQ) method which is used to determine the amount of inventory using purchase data. The results of the Apriori Algorithm calculation using sales transaction data from October 2018 to March 2019, namely items that have the highest and strongest relationship or similarity are Vitacimin and Masks with a support value of 34.71% and a confidence value of 76.36%. In the Economic Order Quantity (EOQ) method, the average point of ordering goods is 103 strips with a purchase frequency of three times for six months, and recycling orders again after 70 days.