Data Mining Application Analyzing Customer Purchase Patterns Using The Apriori Algorithm

Authors

  • Moh. Lambang Prayugo Universitas Dian Nuswantoro
  • Dibyo Adi Wibowo Universitas Dian Nuswantoro
  • Moch. Sjamsul Hidajat Universitas Dian Nuswantoro
  • Ery Mintorini Universitas Dian Nuswantoro
  • Rabei Raad Ali University of Mosul

DOI:

https://doi.org/10.33633/jais.v9i1.10308

Abstract

The study aims to implement Data Mining with Apriori Algorithm and Association Methods (shop cart analysis) to analyze the sales pattern of Kaffa Beauty Shop stores as a case study. Sales information obtained from stores is used to find out the repeated buying habits of cosmetic products. This analysis provides store owners with valuable information to make more useful decisions about product inventory management, marketing strategies, and other aspects of their business. The Apriori Algorithm implementation follows steps including data preprocessing, subsetting, frequent dataset search, and strong association rules (strong Association Rules). The results of the analysis show that there are important purchasing patterns among some cosmetic products that can be the basis of a more effective sales strategy. The study helps understand how data mining and Apriori Algorithms can be applied in business contexts such as Kaffa Beauty Shop stores. Therefore, the results of this analysis are expected to contribute greatly to improving business efficiency and optimizing marketing strategies for store owners and stakeholders. The research is also expected to show the enormous potential of data analysis to support optimal business decision making.

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Published

2024-04-02

Issue

Vol. 9 No. 1 (2024): Journal of Applied Intelligent System

Section

Articles

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