Implementasi Algoritma Apriori Pada Transaksi Penjualan Berbasis Web

Abstract

Goodmend Store, located on Jalan Raya Serang, Tangerang Regency, experienced a decrease in monthly revenue due to competition in the clothing industry. So far, sales transaction records have only been archived without further use, even though this data has great potential to increase sales and produce new products. This research aims to develop a web-based application using an a priori algorithm to analyze sales transaction data and understand customer purchasing patterns. With a minimum support of 4% and a minimum confidence of 30%, eight association rules were found, one of which showed that 35.42% of consumers who bought Shorts also bought Long Pants. The results of this research provide insight into products that customers frequently purchase together, allowing stores to make better business decisions and increase sales. With this system, Goodmend Store is expected to increase its sales by understanding customer purchasing habits and providing optimal product recommendations.