Indonesian Journal of Artificial Intelligence and Data Mining
Vol 8, No 1 (2025): March 2025

Clothing Inventory Forecasting System at Kagas Using the Weighted Moving Average Method

Sulistiani, Indah (Unknown)
Sembiring, Muhammad Ardiansyah (Unknown)
Akmal, Akmal (Unknown)



Article Info

Publish Date
04 Nov 2024

Abstract

Information systems are made in stores so that they can easily process data and produce the information needed quickly, accurately, precisely, effectively and efficiently in spending costs. Kagas is a clothing store engaged in fashion that has been established since 2020. The purpose of this study is to apply the Weighted Moving Average method to the forecasting system in determining sales of robe clothes.  The results of calculating the stock of gamis clothes manually and calculating using a forecasting system using the previous year's data from May 2023 to April 2024 are the same. Forecasting of gamis clothes for the May 2024 period is 175 with a MAD value of 8.04, an MSE value of 135.33 and a MAPE value of 4.7%. With a forecasting system using the weight moving average method, it makes it easier for Toko Kagas to forecast the stock of gamis clothes inventory in the following month.

Copyrights © 2025






Journal Info

Abbrev

IJAIDM

Publisher

Subject

Computer Science & IT

Description

Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM) is an electronic periodical publication published by Puzzle Research Data Technology (Predatech) Faculty of Science and Technology UIN Sultan Syarif Kasim Riau, Indonesia. IJAIDM provides online media to publish scientific ...