Apriori Algorithm For Analyzing Supermarket Shopping Transactions At Xyz Store

Abstract

Every company or organization must make the right business strategy to achieve the desired target. The result of each sales data in a company is the occurrence of data that is accumulated and centralized in a database. This is a very useful thing to be able to do an analysis. Many variations of goods are traded, and based on that, it will affect a person's mindset to get products that have similar consumption patterns, find out which products have the highest sales prices and the relationship between customer buying interest in a product and other products. Requires one method. With a priori methods, products that appear can be known simultaneously. A priori methods are included in association rules in data mining. One phase of the method of analyzing the connectedness of a product that is currently applied by researchers in creating a good algorithm is by analyzing frequency patterns. The importance of product relatedness can be identified by two parameters, namely: support and confidence. Support (support value) is the percentage of combinations of items in the database, while confidence (certainty value) means a strong correlation between items in the law of association. a priori solution procedures can help the development of marketing management.