RANCANG BANGUN APLIKASI DATA MINING UNTUK MARKET BASKET ANALYSIS DENGAN ALGORITMA APRIORI - Yono Cahyono (Jurnal Informatika Universitas Pamulang, 2022)
Data on very large sales transactions have information on consumer purchasing patterns for data mining processes. Market Basket Analysis is the process of analyzing transaction data to determine what products are most often purchased by consumers and to find associations and correlations between these items. Based on these problems, a system is needed to manage data on sales of goods transactions, based on trends that appear simultaneously in a transaction using the Apriori Algorithm. The Apriori algorithm is a data mining association rule whose purpose is to find the rules for a combination of an item by calculating the support and confidence values. By using the Apriori Algorithm, it is possible to bring up products based on frequent value calculations of a product with other products based on consumer purchase transactions. The use of the algorithm is expected to find consumer buying patterns. The results achieved are in the form of reports on the results of data mining patterns of purchasing goods that are often purchased simultaneously in order to determine marketing strategies in selling goods. Keywords: data mining; market basket analysis; apriori algorithm.