JOMLAI: Journal of Machine Learning and Artificial Intelligence
Vol. 1 No. 4 (2022): December

Application of Data Mining on Patterns of Sales of Goods in Minimarkets Using the Apriori Algorithm

Siti Hadija (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
Eka Irawan (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
Irfan Sudahri Damanik (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
Jaya Tata Hardinata (Universitas HKBP Nommensen Pematangsiantar, Indonesia)



Article Info

Publish Date
30 Dec 2022

Abstract

Minimarket is a shop that sells goods for daily needs. Each minimarket generates a lot of sales data every day. Sales transaction data can only be stored without further analysis. Based on this description, research was conducted to assist minimarket managers in making it easy to solve sales pattern problems at minimarkets using the Apriori algorithm. The Apriori algorithm is an algorithm that searches for item set frequencies using the association rule technique. The final result of using data mining using the Apriori association method is proven to be able to find out the results of the analysis that appear simultaneously based on sales data at the Mawar Simp.Tangsi Balimbingan Minimarket with a minimum amount of support of 30% and 80% confidence resulting in 8 association rules that are formed.

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Journal Info

Abbrev

jomlai

Publisher

Subject

Computer Science & IT Engineering

Description

Focus and Scope JOMLAI: Journal of Machine Learning and Artificial Intelligence is a scientific journal related to machine learning and artificial intelligence that contains scientific writings on pure research and applied research in the field of machine learning and artificial intelligence as well ...