Implementing Moving Average Forecasting System for Apparel Sales: Predicting Inventory Needs with Enhanced Accuracy

Abstract

Forecasting the supply of goods is one of the company's planning strategies to increase sales. However, there are several obstacles in forecasting the supply of goods in one of the boutiques in Jember Regency such as manual sales data collection, namely by recording clothing sales data in the sales book. So that there can be errors in predicting the supply of goods in the future. The purpose of this study is to apply a clothing sales forecasting system using the moving average method to forecast the supply of goods. This study applies the waterfall model to build a system with stages of analysis, design, implementation and testing. Analysis will be carried out by collecting data related to system requirements through observation, interviews and literature studies. While at the design stage there are usecase diagrams and system flow diagrams. Furthermore, the implementation stage was carried out in boutiques in Jember Regency by piloting the boutique owners. System testing uses black box testing to ensure there are no system functional errors. The findings show that the system in the form of a website can be run properly and can be accessed as long as there is an internet network. In addition, our system is already running well based on the results of black box testing. So that this system can be used by companies as forecasting considerations in providing inventory of goods.