ANALISA POLA TRANSAKSI PEMBELIAN KONSUMEN PADA TOKO RITEL KESEHATAN MENGGUNAKAN ALGORITMA FP-GROWTH

Abstract

Competition in the world of retail business today requires companies to continue to find various kinds of strategies and creativity in running a business. CV Harmoni Medicine Indonesia is a retail company engaged in the sale of health and beauty products. One of the business strategies that can be done is cross-selling or offering other products that have a relationship with the product purchased so that it can increase sales. This study aims to analyze consumer purchases by looking at the relationship between products that are often purchased. The data used in this study is sales transaction data of CV Harmoni Medicine Indonesia for 3 years from January 1, 2020, to December 31, 2023, which has 9,844 data rows and 10 attributes. The method used in this study uses an association data mining approach with the Frequent Pattern Growth (FP-Growth) algorithm which has a process stage starting from collecting sales transaction data, selecting relevant attributes, preprocessing data, dataset association process, and evaluating patterns formed. The determination of the association pattern uses the minimum value of support, the minimum value of confidence, and the minimum value of lift. Based on the test results, 9 association rules were formed using the minimum value of Support = 0.005, the minimum value of Confidence = 0.1, and the minimum value of Lift = 1.0, with 9 forming products. Association rules formed using the FP-Growth algorithm can help cross-selling sales strategies be easier and more efficient by providing detailed information on consumer product purchase patterns with a high chance of success.