Implementasi Data Mining Untuk Menentukan Produk Buku Komik Terlaris Pada Toko Arivpedia Menggunakan Algoritma Apriori
DOI:
https://doi.org/10.31599/2gd01j83Keywords:
Apriori Algorithm, Comic Books, E-commerce, Data Mining, ArivpediaAbstract
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.
Downloads
Downloads
Published
Issue
Section
License
Please read and understand the copyright terms for submissions to this journal.
Copyright Notice
TheĀ Jurnal Keamanan NasionalĀ is under the Creative Commons Attribution 4.0 International (CC-BY 4.0) License, according to which:
1) Authors retain copyright and grant the journal the right to first publication, with the work simultaneously licensed under the Creative Commons Attribution (CC-BY 4.0) that allows the sharing of articles published with the acknowledgement of authorship and the initial publication in this journal.
2) The authors are authorized to make additional contracts separately for distribution of the version of the work published in this journal (for example, publication in an institutional repository or as a chapter of the book), as long as there is recognition of authorship and initial publication in this journal.
3) Authors are authorized and encouraged to publish and distribute their work online (for example, in institutional repositories or on their personal pages) at any time before or during the editorial process, as it increases the impact and reference of the published work.