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Implementasi Data Mining untuk Analisis Data Penjualan dengan Menggunakan Algoritma Naïve Bayes

Year: 2024

Type: article

Abstract: KPRI KOKARNABA Baturraden faces challenges in managing increasingly complex sales data, particularly in identifying the most in-demand products to maximize profit. This study aims to analyze sales patterns using the Naïve Bayes algorithm as a probability-based classification method. The collected sales data were analyzed to identify categories of best-selling and less popular products within the cooperative. The results indicate that the Naïve Bayes algorithm has an accuracy rate of 77.56% in predicting product categories. This research is expected to assist the cooperative in optimizing stock management and improving member satisfaction.

Source: Merkurius Jurnal Riset Sistem Informasi dan Teknik Informatika

DOI: 10.61132/merkurius.v2i6.475

Authors: Lifa Sholiah, Ito Setiawan, Abdillah Teguh Permana, Iqbal Yusuf Azhari, Wakhid Sayudha Rendra Graha Alrashid

Institution: Universitas Amikom Purwokerto

Language: English

Topic: Data Mining and Machine Learning Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4404337346

FWCI: 0.387

Cites:

Cited by: 1

Related to: 10