Penerapan Data Mining Untuk Memprediksi Ketersediaan Stok Produk HNI HPAI Menggunakan Algoritma C4.5

Authors

  • Murlena Murlena Universitas Pat Petulai, Bengkulu-Indonesia, Indonesia
  • Diwi Apriana Universitas Pat Petulai, Bengkulu-Indonesia, Indonesia

DOI:

https://doi.org/10.29240/arcitech.v2i1.5271

Keywords:

Data Mining, Algorithm C4.5, Stock, HPAI

Abstract

In a company, the availability of this stock must be considered to avoid product losses caused by expiration and also to avoid order cancellations. The data contained in the HPAI company application, called the HSIS application, can be utilized and applied for data mining in determining which products are in demand in everyday life. This HSIS application can be used by the Business Center (BC) and all Stock Agents in the HPAI HNI business. To maintain the availability of product stock, the purpose of this study is to test the Stock Agent using the C4.5 Algorithm to predict that the availability of products that must be maintained is in accordance with customer needs. The use of the C4.5 algorithm on stock agents can overcome stockpiling and finance or stock agents capital can be used to buy stock that must be available. The results of the analysis using the C4.5 algorithm stated that although the price of the product was expensive, it was still selling well as herbal products. So of the three types of HPAI HNI products (Herbs product, Health food & beverage and Cosmetic & home care), the stock that must be increased or available is the Herbs Product.

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Author Biographies

Murlena Murlena, Universitas Pat Petulai, Bengkulu-Indonesia

Fakultas Teknik, Prodi Ilmu Komputer

Diwi Apriana, Universitas Pat Petulai, Bengkulu-Indonesia

Fakultas Teknik, Prodi Ilmu Komputer

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Published

30-06-2022

How to Cite

Murlena, M., & Apriana, D. (2022). Penerapan Data Mining Untuk Memprediksi Ketersediaan Stok Produk HNI HPAI Menggunakan Algoritma C4.5. Arcitech: Journal of Computer Science and Artificial Intelligence, 2(1), 19–32. https://doi.org/10.29240/arcitech.v2i1.5271

Issue

Vol. 2 No. 1 (2022): June 2022

Section

Articles

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