Apriori Algorithm Analysis of Purchase Pattern Prediction on CV. Askara Media Literature

Authors

  • Yoga Fitriana Universitas Pembangunan Panca Budi
  • Muhammad Syahputra Novelan Universitas Pembangunan Panca Budi
  • Muhammad Iqbal Universitas Pembangunan Panca Budi

Keywords:

Data Mining, Apriori algorithm, Purchasing pattern, Association rule, Sales

Abstract

This study aims to analyze consumer purchasing patterns at CV. Askara Sastra Media by utilizing data mining techniques with the A priori algorithm. The data used consists of sales transaction data that has undergone preprocessing to ensure data quality and consistency. The Apriori method is applied to discover frequent itemsets and generate association rules based on support and confidence values. The results show that the A priori algorithm is capable of identifying relationships between products that are frequently purchased together, with several association rules having high confidence and lift values. The resulting purchasing patterns provide valuable insights for the company in determining marketing strategies, such as product bundling and product placement. Therefore, the implementation of the A priori algorithm is proven to be effective in supporting data-driven decision-making and improving sales strategy efficiency at CV. Askara Literature Media.

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Published

2025-10-27

Issue

2025: Proceedings of International Conference on Islamic Community Studies

Section

Articles

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Copyright (c) 2025 Yoga Fitriana, Muhammad Syahputra Novelan; Muhammad Iqbal

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