Jurnal Informatika: Jurnal Pengembangan IT
Vol 8, No 2 (2023): JPIT, Mei 2023

Komparasi Metode Apriori dan FP-Growth Data Mining Untuk Mengetahui Pola Penjualan

Neni Purwati (Institut Informatika dan Bisnis Darmajaya)
Yogi Pedliyansah (Institut Informatika dan Bisnis Darmajaya)
Hendra Kurniawan (Institut Informatika dan Bisnis Darmajaya)
Sri Karnila (Institut Informatika dan Bisnis Darmajaya)
Riko Herwanto (Institut Informatika dan Bisnis Darmajaya)



Article Info

Publish Date
29 May 2023

Abstract

 Sales data is generally still rarely used, as well as the Perfume Corner shop just piling up in the database, even though there are problems experienced by the store regarding sales data for the best-selling products and to increase the number of sales of subsequent perfume products, so that the store can survive and develop even better. The algorithm that can be used to manage sales data to overcome this problem is Apriori. The research method used in this research is the KDD (Knowledge Discovery in Database) process. This research produces a high frequency pattern for itemsets with a minimum support value of 20% resulting in products that become The Most Tree Items namely Jo Malone 82.49%, Zarra 28.25%, and Zwitsal 20.34%. While the association rules formed from the value of Min. Supp 20% and Min. Conf 80%, get a combination of 2 itemsets, namely Jo Malone and Zarra. Whereas for the combination of 3 itemsets, namely Jo Malone, Zarra and Baccarte with valid and strong status, it is proven by a lift value greater than 1, therefore the association rules are very appropriate to be used.

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Journal Info

Abbrev

informatika

Publisher

Subject

Computer Science & IT

Description

The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance ...