Market Basket Analysis Apotek Berbasis Web Menggunakan Metode Algoritma Apriori

Authors

  • Vicky Syahrul Bashiir Universitas Mercu Buana Yogyakarta Author
  • Arita Witanti Universitas Mercu Buana Yogyakarta Author

Keywords:

Market Basket Analysis, Apriori Algorithm, Association Mining

Abstract

Market Basket Analysis (MBA) is a data analysis technique employed to discern concurrent purchasing patterns within a transactional dataset. Within the pharmaceutical industry, an MBA can be harnessed to comprehend customer purchasing habits and formulate more efficacious marketing strategies. In this study, the researchers propose a web-based Market Basket Analysis system tailored for pharmacies. This system utilizes the Apriori algorithm, a prominent algorithm for association mining. The Apriori algorithm facilitates the identification of significant item sets and association rules from transactional datasets. The proposed system empowers users, such as pharmacy proprietors or store managers, to interactively analyze transactional data through a web interface. Users can upload transactional datasets into the system and specify parameters, for instance, the minimum support value and confidence level. Subsequently, the Apriori algorithm generates significant item sets and association rules based on the stipulated parameters. Through this system, users can garner insights into customer purchasing patterns, frequently co-purchased products, and association rules that can be leveraged to enhance marketing and sales strategies.

 

 

 

Author Biography

  • Arita Witanti, Universitas Mercu Buana Yogyakarta

    Informatics

References

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Published

2024-06-07

How to Cite

Market Basket Analysis Apotek Berbasis Web Menggunakan Metode Algoritma Apriori. (2024). Informatics and Artificial Intelligence Journal, 1(2), 59-64. http://jurnal.forai.or.id/index.php/forai/article/view/7