Perbandingan Metode SMA dan MWA Dalam Memprediksi Jumlah Penjualan Alat Olahraga
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Shella Syafira
*
STMIK Royal Kisaran, Kisaran,
Indonesia
- Jeperson Hutahaean STMIK Royal Kisaran, Kisaran, Indonesia
- Santoso Santoso STMIK Royal Kisaran, Kisaran, Indonesia (*) Corresponding Author
Abstract
Taufik Sport shop is a store engaged in the sale of sports equipment, located in West Kisaran City, Asahan Regency. Every day many sales transactions occur at the Taufik Sport Kisaran Store, which of course will affect the supply of sports equipment in the warehouse. The problem faced by the Taufik Sport Kisaran Store is the difficulty in predicting the number of sports equipment that must be available in the following month in order to meet customer demand and not cause the accumulation of goods in the long term. The forecasting process has been carried out only based on estimates by looking at the sales data recap of the previous month. Therefore, it is necessary to build an application for forecasting sales of sports equipment using the Single Moving Average method and the Weighted Moving Average method to get more accurate forecasting results. The data used for this study is data on sales of sports equipment from March 2021 to February 2022. This study aims to compare the Single Moving Average and Weighted Moving Average methods in predicting sales of sports equipment and determine the level of accuracy of the two methods. The Weighted Moving Average method is a method that uses a technique of giving different weights to the available data with the thought that the most recent data is the most relevant data for forecasting so that it is given a greater weight, while the Single Exponential Smoothing method does not use weighting in forecasting calculations but take the average value of the price of a sale in a certain time range back. The results of this study are based on the MAPE value, the WMA method is better than SMA because it is more suitable for forecasting fluctuating sports equipment sales data. The comparison indicator is seen from the forecasting accuracy by finding the smallest error value between the two methods
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