Selection for the best ETS (error, trend, seasonal) model to forecast weather in the Aceh Besar District

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Chesilia Amora Jofipasi, Miftahuddin, Hizir

2018 IOP Conference Series: Materials Science and Engineering Vol. 352 Issue 1 Conference paper Cited by 17 SDG 13 Quartile

Abstract

Weather is a phenomenon that occurs in certain areas that indicate a change in natural activity. Weather can be predicted using data in previous periods over a period. The purpose of this study is to get the best ETS model to predict the weather in Aceh Besar. The ETS model is a time series univariate forecasting method; its use focuses on trend and seasonal components. The data used are air temperature, dew point, sea level pressure, station pressure, visibility, wind speed, and sea surface temperature from January 2006 to December 2016. Based on AIC, AICc and BIC the smallest values obtained the conclusion that the ETS (M, N, A) is used to predict air temperature, and sea surface temperature, ETS (A, N, A) is used to predict dew point, sea level pressure and station pressure, ETS (A, A, N) is used to predict visibility, and ETS (A, N, N) is used to predict wind speed. © Published under licence by IOP Publishing Ltd.

Affiliations

Department of Statistics, Faculty of Mathematics and Science, Syiah Kuala University, Banda Aceh, Indonesia

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