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Prediction of rainfall using ARIMA mixed models
Journal
Applied Mathematics and Computational Intelligence (AMCI)
Date Issued
2021-12
Author(s)
Miftahuddin
Universitas Syiah Kuala
Norizan Mohamed
Universiti Malaysia Terengganu
Maharani.A. Bakar
Universiti Malaysia Terengganu
Nur Shima
Indonesian School for Meteorology Climatology and Geophysics
Fadhli
Syiah Kuala University
Ichsan Setiawan
Syiah Kuala University
Abstract
The average rainfall in Aceh Baratevery year is different pattern and it is influenced by several factors. In this paper we used rainfall dataset, which is changing time to time. The change is caused byan element of fluctuate and volatility in the data. The purpose of this study was to find the best ARIMA mixed models as combination with ARCH and GARCH models.The data used in this study are rainfall data and the number of rainy days in Aceh Barat district from the period January 2008 to December 2017. The results showed that stationary rainfall in the transformation results of Zt0.27 and the first differencing (d=1) and test results Lagrangemultiplier-ARCH for rainfall data and the number of rainy days shows significant lag 4. The best model for predicting rainfall uses the ARIMA(2,1,0)-ARCH(3) model and for the number of rainy day using the ARIMA(2,0.2) model. The calculation results obtained prediction accuracy value for rainfall using ARIMA(2,1,0)-GARCH(1,3) model with MAD, RMSE, MAE,and MASE values of 1,175, 1.163, 0.941and 0.720respectively and for the number of rainy days using ARIMA(2,0,2) model were accuracy value respectively 4.448, 3.849, 3.189and 0.737.
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