Forecasting Performance of Double Exponential Smoothing Model and ETS Model for Predicting Crude Oil Prices

Hari Prapcoyo (Jurusan Informatika, Universitas Pembangunan Nasional "Veteran" Yogyakarta)
Mohamad As'ad (STMIK PPKIA Pradnya Paramita)
Sujito Sujito (STMIK PPKIA Pradnya Paramita)
Sigit Setyowibowo (STMIK PPKIA Pradnya Paramita)
Eni Farida (STMIK PPKIA Pradnya Paramita)

Telematika : Jurnal Informatika dan Teknologi Informasi
Vol 20, No 2 (2023): Edisi Juni 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.