PENERAPAN KAIDAH ASOSIASI PADA DATA TRANSAKSI MINIMARKET DENGAN MENGGUNAKAN ALGORITMAFREQUENT PATTERN GROWTH (FP-GROWTH)

Abstract

Transaction data are stored only as many records can provide useful knowledge in making policies and marketing strategies for the mini market KOCIKA UNESA in State University of Surabaya Ketintang. For that purpose one can apply the techniques of DATA MINING association rules. Association rules is a procedure to search for knowledge in the form of consumer purchasing patterns. This pattern can be input in making policy and marketing strategy. A pattern is determined by two parameters, namely support (support value) and confidence (certainty value). This association rules using frequent growth algorithm (FP-growth) by applying the FP-tree data structure to find the purchase patterns. One pattern resulting from the analysis of transaction data last 1 month with 23 categories of items that if buy detergent, buy soap too with support = 19% and = 75% confidence value.
Keyword: Transactions data, Association rules, FP-growth