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Forecasting of Primary Energy Consumption Data in the United State: a comparison between ARIMA and Holter Winters Models

Abdul Rahman and Ansari Saleh Ahmar
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Ansari Saleh Ahmar: Universitas Negeri Makassar

No snxrq, INA-Rxiv from Center for Open Science

Abstract: 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). Paper ini dipresentasikan pada The 3th International Conference on Green Design and Manufacture 2017 (Krabi, Thailand, 29-30 April 2017), diunggah oleh Ansari Saleh Ahmar

Date: 2017-08-30
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Persistent link: https://EconPapers.repec.org/RePEc:osf:inarxi:snxrq

DOI: 10.31219/osf.io/snxrq

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