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Apriori Algorithm to Predict Availability of Beauty Products

Authors

  • Maria Hikmah Hasibuan Computer Science Department, Universitas Islam Negeri Sumatera Utara, Medan, Indonesia
  • M.Fakhriza Computer Science Department, Universitas Islam Negeri Sumatera Utara, Medan, Indonesia

DOI:

10.47709/cnahpc.v6i3.4259

Keywords:

Data Mining, Apriori Algorithm, Beauty Products, Inventory Management, Consumer Behavior

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Abstract

This study introduces the Apriori algorithm in beauty product availability prediction system as a solution to enhance stock prediction accuracy and mitigate inventory risks in the beauty industry. By applying data mining technology, specifically the Apriori algorithm, Kazana Kosmetik aims to gain insights into consumer purchasing patterns to optimize operations. The research analyzes transaction data to identify key buying patterns and improve stock management strategies. The results reveal seven main purchasing patterns with an average confidence value of 0.414, offering valuable guidance for Kazana Kosmetik in inventory control and marketing tactics. By leveraging data mining techniques, companies like Kazana Kosmetik can streamline sales strategies and enhance customer satisfaction. This research underscores the effectiveness of the Apriori algorithm in predicting beauty product availability and its potential to revolutionize operational efficiency in the cosmetics market.

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References

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ARTICLE Published HISTORY

Submitted Date: 2024-07-09
Accepted Date: 2024-07-09
Published Date: 2024-07-27

How to Cite

Maria Hikmah Hasibuan, & M.Fakhriza. (2024). Apriori Algorithm to Predict Availability of Beauty Products. Journal of Computer Networks, Architecture and High Performance Computing, 6(3), 1232-1244. https://doi.org/10.47709/cnahpc.v6i3.4259