Forecasting Performance of Double Exponential Smoothing Model and ETS Model for Predicting Crude Oil Prices - Prapcoyo, Hari; As'ad, Mohamad; Sujito, Sujito; Setyowibowo, Sigit; Farida, Eni (Jurusan Informatika, 2023)
Purpose: This study aims to predict the price of monthly crude oil quickly and accurately by using an easy model and with easily available software.Design/methodology/approach: This study compares the DES-Holts and ETS models to predict price of monthly crude oil.Findings/result: The results of this study recommend the ETS(M,N,N) model to predict the price of monthly crude oil which produces an accuracy value of RMSE and MAPE of 4.385812 and 6.499007 %, respectively.Originality/value/state of the art: This study implements the DES_Holt's and ETS models to predict price of monthly crude oil with an RMSE and MAPE forecasting accuracy that has never been done in previous studies.