Analisis Pola Pembelian Konsumen pada Data Transaksi Penjualan Suku Cadang Mobil dengan Algoritma FP-Growth (Studi Kasus: PT. Sun Star Motor Kudus)

Abstract

PT. Sun Star Motor Kudus is an automotive company by providing genuine spare parts to consumers. PT. Sun Star Motor Kudus has a database system that is integrated with a computer due to the large number of transactions within a certain period of time. Transaction data can be processed with data mining science to get hidden information. For this reason, data transactions will be processed using the association rule. This rule is used to generate a combination of items from all transactions within 1 year. By applying the FP-Growth algorithm in Kaggle, several combinations of items that are frequently purchased are found, namely 1) Grease/Vit Paslin and Oil Filter Canter 2) Diesel Engine Oil L300 and Grease/Vit Paslin 3) Oil Ring and Diesel Engine Oil L300 4) Engine Oil L300 Diesel and L300 Oil Filter 5) L300 Diesel Engine Oil and Accu Water. With the combination of these itemset, PT. Sun Star Motor Kudus can increase profits by using this information. For example, providing an attractive promo if a customer buys a combination of the itemset.