ANALISA POLA PEMBELIAN PRODUK DENGAN MENGGUNAKAN METODE FP-GROWTH PADA TOKO HERON - Muhammad Aldi Zarkashy; Ria Rismayati; Ismarmiaty, Ismarmiaty (Yayasan Nuraini Ibrahim Mandiri, 2024)
Technological developments have had an impact on all activities including retail business. Utilization of managed data can provide information that can be used to improve the quality and effectiveness of buying and selling business activities. One of the patterns analyzed in the retail business sector is the pattern of product sales linkages using association algorithms in data mining using the FP-Growth algorithm. The aim of this research is to find association patterns in purchasing behavior at Heron stores to help make policies in better product inventory management and also increase sales and product promotions at Heron stores. This research uses applied research methods with stages of Data Collection and Preparation, Application of the FP-Growth Method, Testing Results and Conclusions. The conclusion of this research is that the results of pattern analysis provide 13 rules in accordance with minimum support, minimum confidence and minimum lift ratio as strong rules and are expected to help and support decisions from the Heron store. This also has a positive impact on the benefits of technology which can provide information from sales archive data that can be used to improve service and sales in retail businesses, especially at Heron stores.