Implementation of the Market Basket Analysis Method on Sales Transaction Data Using the CT-Pro Algorithm

Authors

  • Achmad Davit Adi Supriyatna
  • Hidayatulah Himawan
  • Wilis Kaswidjanti

Abstract

Purpose: Produce data mining applications to find out the combination of items with the highest frequency so that customer purchasing patterns are known.
Design/methodology/approach: Using the Market Basket Analysis method with the CT-Pro Algorithm. System development using the Waterfall method.
Findings/result: From the data for 3 months, 18 tests were carried out with minimum support and minimum confidence, starting from the system default value until no more rules were found. Until finally, the maximum limit for determining the minimum support was 12% and the minimum confidence was 40%, and from the 18 tests, the one with the best emergence value was "If buy 1Kg Eggs, then buy 1Kg Granulated Sugar", the confidence value is 41,86% and the lift ratio is 2,06.
Originality/value/state of the art: The difference between this research and previous research is in the object section. This study uses sales transaction data at Bambang’s shop, which is located in Kebumen. The output of this system is the result of association rules that meet the minimum support and minimum confidence values.

Published

2026-01-22

Issue

Vol. 2 No. 1: May 2022

Section

Articles

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