PEMODELAN DAN FORECASTING KEBUTUHAN AIR BERSIH DI PROPINSI DIY MENGGUNAKAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)
Kata Kunci:ARIMA, Forecasting, Clean Water Need, SSR, AIC
AbstrakThe need of clean water will be something that is expensive in the future. Because of that reason, the focus of this research is the forecasting of clean water need in DIY. The purpose of this research is to find the best model and suitable with the data that will be used in the forecasting. The data of forecasting can be used by the people as the alternative solution to anticipate the possibility and the based reason to make regulation. The meodel that would be employed is ARIMA with the step of preprocessing, model identification, model estimation and diagnostic check and forecasting. The best model after data analyzing is ARIMA (1,1,0) with the Sum squared resid of 0,330933, Akaike info criterion of 1.050808, Schwarz info criterion of -0.951235, that best model will be employed to conduct forecasting some steps ahead. The result of clean water need forecasting in the next 5 years is 2016: 138.840,9, 2017: 138.000,8, 2018:138.400,6, 2019: 138.209,9 and 2020: 138.300,8 in thousand meter cubic
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