Implementasi Algoritma Apriori Untuk Menentukan Stok Barang Gudang Pada Toko Bangunan Jaya Gemilang

Abstract

The aim of this research is to analyze goods sales transaction data and the system for implementing the Apriori algorithm at the Jaya Gemilang Building Store, Pagar Alam City. The problem in this research is that the current sales process at the Jaya Gemilang Building Store is carried out manually, that is, where to view the sales transaction data for goods. which are often purchased and which are rarely purchased by consumers and analysis of goods sales transaction data still uses book records, causing a lack of control over the supply of goods in shops and making it difficult to know which goods consumers buy a lot. This Aprior algorithm is very effective in finding relationship patterns between one or more itemsets in a large data set so that it is effective in calculating sales transaction data and determining consumer habit combination patterns so that they can find out which drugs are often used. The process of applying the Apriori algorithm to goods sales transaction data at the Jaya Gemilang building store using the raptdminer application, is the same as the results in a system built using 7 months of drug sales transaction data using a minimum support of 20% and a minimum confidence of 40%. So from this research information was obtained that goods that were often purchased together during 7 months were 11 combinations of 2 items that met the minimum confidence value of 40%, which in turn was goods that met the confidence value, the shop could provide more stock at the Jaya Gemilang building store, Pagar Alam City.