Analisis Peramalan Demand Produk RBL dengan Metode Double Exponensial Smoothing, Moving Avarage, dan Regresi Linear di PT Seiwa Indonesia - Azizah, Nada Nishi; Nisah, Firda Ainun (LPPM Universitas Pahlawan Tuanku Tambusai, 2024)
Based on historical data on the number of product requests and products produced in the January 2021-December 2022 period, there is a considerable discrepancy. Therefore to be able to predict demand in one or several subsequent periods based on past product demand data, the researcher conducts a forecasting analysis using the double exponential smoothing, moving average, and linear regression methods to find out the most accurate forecasting method to use. Based on the calculation results, it can be concluded that the most appropriate Forecasting method is the linear regression method because it has the lowest MSE value of 1,346,936,387. It is hoped that it will be able to assist PT Seiwa Indonesia in providing future stocks of RBL products in more accurate manner so as to reduce losses due to excessive production.