Peramalan Stock Barang Dagangan Menggunakan Metode Single Exponential Smoothing

Abstract

Forecasting can be used in any field which requires a prediction of the existence of data in the future. Forecasting can be applied of them to help budget sales for the next period. Time series data obtained from sales data during a certain period of sales of a product can be used as the basis for forecasting. Excessive restocking of goods is not good for a store, because there is a possibility that the purchased goods will not sell well in the future. There needs to be a good control process for restocking goods, one of which can be used is to use a prediction of merchandise restocks using single exponential smoothing (SES). There are two kinds of sales data used, namely Koi Rice with a size of 5 kg and Bimoli Oil with a size of 900 ml. From the results of the SES calculation, a good alpha value for forecasting 5kg Koi Rice is 0.46. While the alpha value for 900ml Bimoli Oil is 0.704. The alpha value is obtained from the calculation of the smallest MSE value. The prediction results show that in the next period (15-30 September 2021) there will be a decrease in the number of sales of goods from the two products, so that shop owners can reduce their shopping allotment.