Penerapan Data Mining Menggunakan Algoritma FP-Growth Untuk Menentukan Pola Pembelian Produk Pada Minimarket Justin Mart

Abstract

This study aims to apply data mining using the FP-Growth algorithm to transaction data from Justin Mart minimarket, to determine the purchasing patterns of consumers. This is because the improper placement of products that do not align with consumer buying behavior and the accumulation of unmanaged data have resulted in uncontrolled inventory at Justin Mart, ultimately affecting product sales. To determine purchasing patterns, the researchers utilized the FP-Growth algorithm to expedite the discovery of frequently occurring itemsets, as this algorithm utilizes the FP-Tree technique to efficiently search for potential itemsets as association rules.The study yields association rules or purchasing rules for products that are frequently bought together by consumers simultaneously using the FP-Growth algorithm. These rules can be employed by the minimarket owner as recommendations for organizing product categories on the same shelf.