Information System Data Mining Market Basket Analysis of Purchase Patterns at Mariden Stores Bandar Lampung - Raynaldi Yudhia (Institute of Computer Science (IOCS), 2020)
The tendency of customers to buy goods at the same time is one of the factors in setting the self-service layout to optimally place goods. A strategic and precise product layout in its arrangement will be more easily accessible by consumers and will not waste time. For this reason, it is necessary to create a system model that can determine product layout patterns in supermarkets by seeking the highest confidence. Data mining is one field that is growing rapidly because of the large need for added value from large-scale databases that are increasingly being accumulated. For this reason, the market basket analysis method is used. The market basket is defined as an itemset that is purchased simultaneously by customers in a transaction. This method begins with calculating the Apriori Algorithm to find a number of frequent itemsets and continues with the formation of association rules. The results will produce rules that are very useful for providing information to Mariden stores about the placement of goods according to consumer consumption patterns, providing convenience to consumers in the process of finding goods to be purchased without having to ask the shop owner, being able to see the stock of goods that will run out and can determine the stock of goods because this can actually affect consumer spending tastes and sales of a product.