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.
