ANALISIS POLA PEMBELIAN KONSUMEN DENGAN ALGORITMA APRIORI PADA PT MULTIBAN OTOSERVIS

Abstract

Data mining is a discipline that studies a technique from patterns, statistics, databases to unearth useful and valuable information. Multi Ban, which is engaged in the sale of merchandise and services, must have sales transaction data. This sales transaction data is often treated only as a record without further processing so that it does not have more use value, from the sales transaction data, information can be known, namely knowing consumer purchase patterns with association rule techniques using the a priori algorithm method. This research utilizes new primary data, namely sales transaction data from Januari to July 2022. The results obtained from the processing of sales transaction data in the form of itemsets with the application of the concept of mining association analysis are known to the value of support in each item, combination of items, confidence value in the formation of frequent itemsets. So, it is known that the most goods are purchased simultaneously by Multiban consumers, This information is very useful for the manager of Multi Ban Otoservis to develop a strategy by increasing the inventory of goods and arranging the layout of the goods close together.