Analysis of Supermarket Product Purchase Transactions With the Association Data Mining Method

Analysis of Supermarket Product Purchase Transactions With the Association Data Mining Method

transaction data’ association rules; data mining; supermarket management; decisions

The development of business world is entering the era of big data. In meeting supermarkets' sales and purchase targets, the
management needs to improve themselves in managing the goods available in the store. The research aims to determine the
pattern of purchases that occur in a transaction, find out related and related products in supermarkets, and improve
supermarket services to customers. The method applied uses the association rules approach to data mining. Several purchasing
data from customers have been able to be analyzed by displaying a diagram as a visualization of the number of specified
association rules. The processing results show a relationship above 90%: sugar and coffee with a confidence of 94.4%, shirts
and trousers with a confidence of 93.4%, and sugar, milk, and coffee with a confidence of 92.0%. Decisions that can be taken
by supermarket management in providing places and goods need to consider and follow product relationships and proximity
based on the highest confidence value to provide services to customers effectively and efficiently

Norbertus Tri Suswanto Saptadi, Phie Chyan, Jeremias Mathias Leda

http://jurnal.iaii.or.id

Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association

June 2026

Sri Wahyuni

ISSN Media Electronic: 2580-0760

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