PERBANDINGAN ALGORITMA FP-GROWTH DAN ECLAT UNTUK ANALISIS POLA PEMBELIAN KONSUMEN PADA TOKO PUTRI FASHION

The sales process in the store "Putri Fashion" produces monthly sales data about what products consumers tend to buy. This happens every month so the data accumulates and the data is not utilized optimally. Make the maximum sales of products in the shop "Putri Fashion". There are also many other products that do not sell and make a loss for the store because of lack of accuracy in product supply selection. This study aims to process these data by utilizing the data mining process by using the association rule technique. The algorithm used is FP-Growth and Eclat because both algorithms are a solution of the Apriori algorithm which has several problems such as having to do pattern matching repeatedly which causes the mining process to be long and for large data to produce many combinations. The results of this study are rules which are the frequent itemset collection with the highest support and confidence values. Used to find products that are more in demand by customers.