Market Basket Analysis of Coffee Shop Customers Using the FP-Growth Algorithm

Abstract

One of the businesses that attracts economic development is a coffee shop. This business is very important and growing rapidly. Shopping cart analysis has the ability to provide information about which products are frequently purchased together. The use of shopping cart analysis is regulated in association rules which is a data processing process that provides records of purchase transactions that come out simultaneously at one time, the algorithm used to regulate these association rules is the FP-Growth algorithm. coffee shop customer shopping cart analysis uses the FP-Growth Algorithm. This research data was obtained from public data on the website https://www.kaggle.com/datasets/sryasuka/coffee-shop-dataset/data,, with a dataset of 1000 transactions, the data processing uses RapidMiner tools, after processing, 2 association rules were found using minimum support = 0.01 and minimum confidence = 0.7. It can be concluded that the results of the shopping cart analysis show that 1 item is most frequently purchased by customers, namely croissants and the purchase of 2 items, namely croissants and fries. So that the shopping basket analysis method with the FP-Growth algorithm can optimize item combination patterns and can improve sales strategies, thereby supporting coffee shop business decision making.