<![CDATA[Cosmetics are products that are often used to beautify one's appearance. CV. Cahaya Sejati, which is one of the providers of cosmetics in Asahan Regency. The cosmetics that were targeted in this study were lipstick, solid powder, shampoo, liquid soap, perfume and handbody with different brands. The results of observations and interviews with the owner of the CV. Cahaya Sejati, cosmetic stock data collection in the warehouse still uses manual recording, so it takes a long time to see the cosmetic stock. In addition, the stock of cosmetics sold for sale so far has sometimes increased with different categories of cosmetics, some increasing and some decreasing. The instability of cosmetic sales makes the owner of CV. Cahaya Sejati has difficulty in determining the amount of cosmetic stock that will be sold in the future. The purpose of this study is to apply the Single Exponential Smoothing method to predict cosmetics in the future. The research method uses the Single Exponential Smoothing method. The stages of the method are cosmetic data collection, data analysis begins with determining the alpha value and calculating the single exponential smoothing method and performing the error accuracy process with MAD, MSE and MAPE. By using the Single Exponential Smoothing method, it will be carried out to predict the stock of cosmetics in the following month, namely March 2022 by using data from March to February 2022. So that the owner of CV. Cahaya Sejati will be able to make a decision in providing cosmetics in the following month. The results showed that in March 2022, Handbody: HBL Liora produced 18.02 with MAPE 22.45%, Lipstick: Dolby produced 22.57 with MAPE 19.36%, Liquid Soap: SPA. Gell yielded 23.10 with a MAPE of 19.27%, Shampoo : Doll yielded 17.26 with a MAPE of 29.25%, and Compact Powder : TWC Dolby yielded 24.74 with a MAPE of 19.91%. So it can be concluded that by applying the single exponential smoothing method, it can be used as a reference for making cosmetic stock decisions at CV. True Light.]]>
