Market Basket Analysis Menggunakan Association Rule dan Algoritma Apriori Pada Produk Penjualan Mitra Swalayan Salatiga

Abstract

Market Basket analysis is learning to manage associations in data processing in various fields. The main purpose of Market Basket analysis in the field of sales is to convey an important message to the company so that it can find out the behavior patterns of entering goods into the shopping basket by consumers so that partners can make a decision. In this study, the Apriori Algorithm is used to take into account changes that occur in the data. This study discusses data mining techniques in analyzing what items are most often purchased at the same time by consumers so that they can change the placement of items that are close together to increase the impulse buying effect. The results obtained are 5 rules where one of the rules obtains the highest confidence value when buying cigarettes, the dominant item is taken simultaneously, namely eggs by obtaining a confidence value that can meet the highest confidence requirements, namely 67%.