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All Journal Jurnal Informatika EDUMATIC: Jurnal Pendidikan Informatika Indonesian Journal of Data and Science Buletin Sistem Informasi dan Teknologi Islam Kajian Ilmiah Mahasiswa Administrasi Publik (KIMAP)
Harlinda, Harlinda
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Mathematics

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Journal : Jurnal Informatika

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Data Mining Approach to Improve Minimarket Sales using Association Rule Method Harlinda, Harlinda; Satra, Ramdan
Jurnal Informatika Vol 12, No 1 (2025): April
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v12i1.20835

Abstract

This research aims to provide recommendations for the placement of goods sold by the UMI Faculty of Computer Science mini supermarket. A data mining approach is used to determine the position of sales items between related items. This is done to make it easier for customers to search for items to buy based on the type of item. Another problem is determining the best-selling items and also determining the types of items that will receive promotions. The data mining approach uses association rules with a priori algorithms. Association rule mining is a data analysis technique used to find patterns and relationships in big data. This technique is widely used in business to help optimize marketing and sales strategies. The results of the rule association using an a priori algorithm show that if consumers buy 200 milli of Ultra Milk Slim Chocolate, they also buy 600 milli of LE MINERAL with a support value of 10% and confidence of 60%. This shows that these two items are related when consumers purchase.
Co-Authors Ariva, Bella Arnoli, Andi Laden Shamil Astuti, Wistiani Darwis, Herdianti Hasanuddin, Tasrif Mansyur, St. Hajrah Mardiyyah Hasnawi Moleo, Alif Safa Muhammad Tahir Muhlis Madani, Muhlis Nasir Nasir Nurfaizah Nurfaizah, Nurfaizah Oihuw, Dewanti Ramdan Satra Syahrir, Alma Umar, Fitriyani