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Penerapan Data Mining untuk Menentukan Produk Terlaris pada PT Joynare Mitra Teknologi menggunakan Metode Naive Bayes Mulyana, Dadang Iskandar; Fadhil, Ali Muhammad
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 2 (2024): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i2.638

Abstract

The research applies the Naive Bayes method to determine the best-selling products at PT Joynare Mitra Teknologi. The contribution of this research is to provide a reference for other companies interested in using similar techniques to analyze their product data. Testing was carried out by processing data using Microsoft Excel and RapidMiner, with training and testing data. The test results show that the Naive Bayes method can classify best-selling products with a high level of accuracy, reaching 87.00%. Apart from that, the resulting precision reached 72.41%, and recall was 80.77%. The best-selling products in hardware sales such as motherboards, CPUs, RAM, hard disks, SSD, and printers can be identified through data analysis. The conclusion from the research is that the Naive Bayes method is very appropriate to use to optimize sales strategies for hardware products based on customer preferences.