Implementasi Algoritma Apriori Untuk Prediksi Pola Penjualan Produk Fashion pada Toko Innari G-Style

Abstract

This research is motivated by the low utilization of transaction data among MSMEs, specifically at Toko Innari G-Style, which still records transactions manually, leading to sales data not being leveraged for strategic analysis. The objective of this research is to develop a web-based sales information system equipped with an analysis feature to identify purchasing patterns using the Apriori algorithm. The research method employs the association rule technique from Data Mining with the Apriori algorithm. Sales transaction data from December 2022 to March 2025 are processed through a pre-processing stage to generate association rules based on support, confidence, and lift values. The result of this research is an information system that successfully and accurately automates transaction recording and reporting. Furthermore, the implementation of the Apriori algorithm successfully identified patterns of frequently co-purchased products, which can be utilized to develop data-driven marketing strategies such as product recommendations and merchandise layout.