ANALISIS POLA PEMBELIAN PRODUK TOSERBA MENGGUNAKAN ALGORITMA FP-GROWTH

Abstract

Advances in technology make business people try to use it to facilitate and advance their business. In line with the development of consumer purchasing power, it requires business people to implement marketing strategies that are better than their competitors. To create a strategy, certain information is needed as material for consideration in making decisions, like determining sales strategies that can utilize information. from a collection of sales transaction data from the Senyum 5000 department store using data mining. Data mining is carried out to analyze the associations between products on the repeat transaction data, while the associations rule technique and the FP-Growth algorithm are part of the data mining used to determine the candidate combinations. The purpose of this study is to determine the result of applying the FP-Growth algorithm to analyze product purchase patterns, find product purchasing rules using the FP-Growth algorithm. This research was conducted on 3,165 transaction data in April-June 2022 with a support value 1% and a confidence value 50% using the Python programming language. The frequent itemset obtained is 17 and the association rules obtained were 21. The association rules obtained were then formed a selling strategy.