A. Rahman, A.S. Ahmar
This research has a purpose to compare ARIMA Model and Holt-Winters Model based on MAE, RSS, MSE, and RMS criteria in predicting Primary Energy Consumption Total data in the US. The data from this research ranges from January 1973 to December 2016. This data will be processed by using R Software. Based on the results of data analysis that has been done, it is found that the model of Holt-Winters Additive type (MSE: 258350.1) is the most appropriate model in predicting Primary Energy Consumption Total data in the US. This model is more appropriate when compared with Holt-Winters Multiplicative type (MSE: 262260,4) and ARIMA Seasonal model (MSE: 723502,2). © 2017 Author(s).
Departement of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Makassar, Daeng Tata Kampus UNM Parangtambung, Tamalate, Makassar, 90223, Indonesia; Departement of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Makassar, Daeng Tata Kampus UNM Parangtambung, Tamalate, Makassar, 90223, Indonesia
