Analisis Keranjang Belanja (Mba) Menggunakan Metode Fp-Growth (Studi Kasus : Minimarket M)

Desy Okta, Suryadiwati (2021) Analisis Keranjang Belanja (Mba) Menggunakan Metode Fp-Growth (Studi Kasus : Minimarket M). Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

The type of retail industry in Indonesia is increasing, one of which is minimarkets. A minimarket with the initials M located in Yogyakarta is a place of business that sells various people's daily needs. Minimaket M has a problem, namely the owner does not know the pattern of purchases that are often made by buyers. The buying pattern has benefits as a marketing strategy for Minimarket M. One of them is knowing what goods are the public's favorite and avoiding losses due to inventory that is less desirable. Researchers will carry out research using Association Rule Mining data mining techniques and the use of Fp-Growth Algorithm. Transaction data is divided into 3 categories, namely product names, types of goods and brands, then divided in detail using a period of seven years, per year, and per month. The minimum support values used are 0.001 and 0.0001. The minimum confidence value used is 0.6. The tool used is Rapid Miner. The results of this study are the rules for the name of the seventh year product as many as 25 rules, the number of rules found for the period per year, in 2019 as many as 15,816, the highest number of periods per month, was in August 2014. the most rules per year period, in 2014 as many as 24 rules, the highest number of periods per month, in July 2014 as many as 36,346 rules. The seventh year brand category produces 15 rules, the highest number of rule periods per year, in 2015 was 3,034, the highest number of periods per month, in August 2014 as many as 535,147. The resulting lift ratio is > 1 or it can be called a positive correlation, which means the occurrence of another occurrence. The benefits of this research, can provide recommendations in finding the right sales package, predict sales, process data into new information, and arrange products on shelves. Keywords: Association Rule Mining, Fp-Growth, Nilai minimum support, Nilai minimum confidence, Lift ratio.

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