Journal of Computation Science And Artificial Intelligence
Vol. 2 No. 2 (2025): Journal of Computation Science and Artificial Intelligence (JCSAI)

METODE WEIGHTED MOVING AVERAGE UNTUK PERAMALAN PENJUALAN TOKO MATERIAL FANS JAYA

Fikran Dzulfikar (Unknown)
Susi Widyastuti (Unknown)
Muhammad Erwanto (Unknown)



Article Info

Publish Date
20 Aug 2025

Abstract

Abstrak Peramalan merupakan elemen penting dalam mendukung pengambilan keputusan bisnis, terutama dalam sektor perdagangan material bangunan yang memiliki dinamika permintaan tinggi. Penelitian ini bertujuan untuk mengembangkan sistem peramalan penjualan menggunakan metode Weighted Moving Average (WMA) pada Toko Material Fans Jaya di Majalengka. Metode WMA dipilih karena kemampuannya memberikan bobot lebih besar pada data terbaru sehingga meningkatkan akurasi prediksi jangka pendek. Penelitian ini menggunakan pendekatan Research and Development (R&D) dengan tahapan analisis kebutuhan, desain sistem menggunakan framework CodeIgniter, implementasi aplikasi web, serta pengujian metode dan program dengan pendekatan Black-box Testing. Hasil implementasi menunjukkan bahwa sistem yang dikembangkan mampu memprediksi penjualan dengan tingkat kesalahan (error) yang relatif kecil dan memberikan manfaat nyata dalam perencanaan stok dan pengendalian biaya. Sistem ini juga membantu mengurangi risiko kelebihan persediaan dan mendukung efisiensi operasional toko. Abstract Forecasting is a crucial component in supporting business decision-making, particularly in the construction materials trade sector, which experiences dynamic demand. This study aims to develop a sales forecasting system using the Weighted Moving Average (WMA) method at Toko Material Fans Jaya, Majalengka. The WMA method was selected due to its ability to assign greater weight to recent data, thus improving short-term prediction accuracy. The research employs a Research and Development (R&D) approach, involving needs analysis, system design using the CodeIgniter framework, web-based application implementation, and testing through Black-box Testing methods. The results demonstrate that the developed system effectively predicts sales with relatively low error rates and provides practical benefits for inventory planning and cost control. The system also helps reduce the risk of overstocking and enhances the operational efficiency of the store

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Journal Info

Abbrev

journal

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science Neuroscience

Description

The Journal of Computation Science and Artificial Intelligence (JCSAI) is a double-blind peer-reviewed journal devoted to publishing original scientific articles on research and development in all fields of Computer Applications. Computational Science is a rapidly growing multi- and ...