Implementasi Data Mining Untuk Menentukan Produk Buku Komik Terlaris Pada Toko Arivpedia Menggunakan Algoritma Apriori

Authors

  • Muhammad Iqbal Iffahuddin Universitas Bhayangkara Jakarta Raya
  • Achmad Noeman Universitas Bhayangkara Jakarta Raya
  • Prio Kustanto Universitas Bhayangkara Jakarta Raya
  • Mayadi Universitas Bhayangkara Jakarta Raya

DOI:

https://doi.org/10.31599/2gd01j83

Keywords:

Apriori Algorithm, Comic Books, E-commerce, Data Mining, Arivpedia

Abstract

How to use transaction data at the arivpedia store selling the best-selling comic book products. Implementing the a priori algorithm to determine the best-selling comic book product pattern in the application to be tested. From this research, according to the analysis and implementation that has been made, the results of an a priori algorithm implementation system are found to determine the best-selling comic book products. With this system at the Arivpedia Store, it helps managers to calculate sales transaction data which is very easy to use. The application of data mining with the a priori algorithm is considered very efficient and can accelerate the process of forming product association patterns from sales transaction data at the Arivpedia store used in the test.

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Published

2024-06-30

Issue

Vol. 5 No. 1 (2024): Juni 2024

Section

Artikel

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How to Cite

Implementasi Data Mining Untuk Menentukan Produk Buku Komik Terlaris Pada Toko Arivpedia Menggunakan Algoritma Apriori. (2024). Journal of Informatic and Information Security, 5(1), 35-44. https://doi.org/10.31599/2gd01j83