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

Authors

  • 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

DOI:

https://doi.org/10.55123/jomlai.v1i4.1668

Keywords:

Apriori, Goods, Data Mining, Minimarket, Sales Pattern

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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Published

2022-12-30

How to Cite

Hadija, S., Irawan, E., Damanik, I. S., & Hardinata, J. T. (2022). Application of Data Mining on Patterns of Sales of Goods in Minimarkets Using the Apriori Algorithm. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(4), 303–312. https://doi.org/10.55123/jomlai.v1i4.1668

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Vol. 1 No. 4 (2022): December

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Copyright (c) 2022 Siti Hadija, Eka Irawan, Irfan Sudahri Damanik

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