ANALISIS DATA MINING UNTUK MENENTUKAN STRATEGI PENJUALAN PRODUK MENGGUNAKAN ALGORITMA FP-GROWTH (STUDI KASUS : MAZAYA OLEH-OLEH PEKANBARU)

Abstract

Mazaya Souvenir Shop Pekanbaru is a company that operates in the culinary sector to be ranked first in the largest culinary industry in Pekanbaru, starting from processing, raw materials, packaging quality and distribution activities. This shop is experiencing difficulties in determining market strategies, one of which is in arranging products purchased simultaneously. The aim of this research is to carry out data mining analysis to determine product sales patterns using the Fp-Growth algorithm. The data used to carry out calculations using the Fp-Growth algorithm must go through several stages such as preprocessing the data, determining minimum support and confidence, determining the frequent itemset header, forming an fp-tree, creating a conditional pattern base based on the fp-tree, and generating frequent itemsets. In this study, a minimum support value of 1% and a confidence value of 80% were used. The research results showed that there were five rules, two frequent itemsets that had a confidence value of ≥80%, namely the products Risol Mayo Lumer and Talam Durian, Risol Ayam and Talam Durian, Red velvet and Talam Durian, Talam Durian and Risol Ayam, Talam Durian and Risol Mayo Lumer.