APLIKASI DATA MINING UNTUK MENEMUKAN ASSOCIATION RULE PADA TRANSAKSI PEMBELIAN BARANG 212 MART MENGGUNAKAN ALGORITMA FP GROWTH

Abstract

The high consumer demand for goods needs at the 212 Mart Tanjung uban supermarket, making transaction data tend to increase every day. Transaction data can be processed using the association rule method via the frequent pattern-growth algorithm found in data mining. In this research, a search for association rules is based on the connectedness of product categories using the method of fp growth algorithm in data mining. The data used in this research are transaction data of products purchased by consumers at 212 Mart Tanjung Uban supermarkets in November 2018-January 2019. The test is done twice, by entering a min support value of 10% and a min confidence value of 50% in the first test, and a min support value of 20% min confidence value of 50% in the second test. Then get the results of the association rule.