Penerapan Metode Weighted Moving Average pada Sistem Peramalan Stok Bahan Laundry

Abstract

Information systems are created in stores so that they can easily make data processing well, and can make predictions or forecasts about stocks that will be prepared in future periods. The purpose of this study is to create and produce a stock forecasting system for laundry materials by applying the Weighted Moving Average (WMA) method. This research is a type of development using a waterfall model by conducting stages of needs analysis, design, implementation and testing. The Analysis phase is carried out to identify the needs used to be applied to this forecasting system. The design stages consist of interface design, flowcharts, use cases and entity relationship diagrams. Implementation and testing are carried out directly using black box testing to see the extent of the functionality of the system that has been created. Our findings show that the system we developed is in the form of a web-based laundry material stock forecasting system. This system is also successful in testing using black box testing, all system components are functioning properly. This system is also calculated accordingly, where the results of the Mean Absolute Percentage Error (MAPE) in detergent stocks get a percentage of 10%, or an accuracy rate of 90%. Meanwhile, the fragrance stock obtained a MAPE yield of 7%, with an accuracy rate of 93%.