Implementasi Algoritma Apriori Terhadap Data Penjualan Untuk Mengetahui Pola Pembelian Konsumen Pada Koperasi Idn Boarding School

Abstract

School cooperatives are established to fulfill common interests and meet the needs of students. The transaction data of a cooperative is increasing day by day, but sometimes in a cooperative the data is left without any further utilization, as happened in the IDN Boarding School Jonggol cooperative. Utilization of the collected data can produce new information that can be used as a reference for cooperatives in determining a business strategy. Therefore, research was conducted on sales transaction data in the IDN Boarding School cooperative as an object to be analyzed using data mining techniques with an a priori algorithm, resulting in a pattern of consumer purchases that occur in the Jonggol IDN Boarding School cooperative. The transaction data used is transaction data at the IDN Boarding School cooperative. This study succeeded in implementing data mining techniques using the a priori algorithm in an application that will be used to process available transaction data, resulting in consumer purchasing patterns that tend to occur from a combination of available items. The association pattern that is formed with a minimum support of 40% and a minimum confidence value of 70% produces 9 association rules. The strong rule obtained is that if you buy a white uniform, you will buy a brown uniform with a support value of 50% and a confidence value of 83.33% items.