Application of Apriori Algorithm to Determine Sales of Traditional Foods

Authors

  • Siti Nurajizah Sistem Informasi Akuntansi Kampus Kabupaten Karawang, Universitas Bina Sarana Informatika
  • Normah Normah Universitas Nusa Mandiri
  • Nurfitriani Nurfitriani Sistem Informasi, Universitas Nusa Mandiri

DOI:

https://doi.org/10.31294/p.v25i1.1840

Keywords:

Data Mining, Algoritma Apriori, Association Rule, Penjualan

Abstract

Competition in the food sales industry is growing, making business owners have to be creative to increase sales turnover. Sales activities that occur every day make sales data increase. Researchers intend to make data on Traditional Restaurant as the basis for data mining processing on food sales using the apriori algorithm. The application of the Apriori Algorithm aims to find the most item combinations based on transaction data and then form association patterns from combinations of items. Association patterns are formed with a minimum support value of 10% and a minimum confidence value of 40% which results in 3 association rules and the most sold food products are Krupuk Bangka and Karedok with a support value of 0.105% and a confidence value of 0.583%

Author Biographies

Siti Nurajizah, Sistem Informasi Akuntansi Kampus Kabupaten Karawang, Universitas Bina Sarana Informatika

 

 

Normah Normah, Universitas Nusa Mandiri

 

 

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Published

2023-03-30

How to Cite

Nurajizah, S., Normah, N., & Nurfitriani, N. (2023). Application of Apriori Algorithm to Determine Sales of Traditional Foods. Paradigma, 25(1). https://doi.org/10.31294/p.v25i1.1840

Issue

Vol. 25 No. 1 (2023): March 2023 Period

Section

Articles

License

Copyright (c) 2023 Siti Nurajizah, Normah Normah, Nurfitriani Nurfitriani

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