BibTex Citation Data :
@article{J.Gauss10239, author = {Siti Hidayah and Agus Rusgiyono and Yuciana Wilandari}, title = {PERBANDINGAN MODEL ARIMA DAN FUNGSI TRANSFER PADA PERAMALAN CURAH HUJAN KABUPATEN WONOSOBO}, journal = {Jurnal Gaussian}, volume = {4}, number = {4}, year = {2015}, keywords = {Rainfall, ARIMA, Transfer Function}, abstract = { Rainfall is one of the things that affect agricultural production. The highest amount of rainfall will cause perturbation in the pollination of flowers and caused zalacca palm to produce fruits no season of the year. Zalacca palm is growing well in heavy rainfall area.. There are some factors which influence rainfall; those are: humidity, solar energy, wind direction and velocity as well as air temperature. The application of ARIMA (Autoregressive Integrated Moving Average) and multi input transfer function was intended to model the rainfall which would be forecasted based on the best model chosen. There were two kinds of variables used in this study. Those were rainfall as the output series while humidity and air temperature as the input series during January 2009 to October 2014. The result showed that ARIMA ([3], 1, [12]) had a fewer Schwart’z Bayesian Criterion (SBC) value 293.199 than multi input transfer function model (0,0,0) (0,1,0) with the result 906.9632. Keywords : Rainfall, ARIMA, Transfer Function}, issn = {2339-2541}, pages = {1037--1044} doi = {10.14710/j.gauss.4.4.1037-1044}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10239} }
Refworks Citation Data :
Rainfall is one of the things that affect agricultural production. The highest amount of rainfall will cause perturbation in the pollination of flowers and caused zalacca palm to produce fruits no season of the year. Zalacca palm is growing well in heavy rainfall area.. There are some factors which influence rainfall; those are: humidity, solar energy, wind direction and velocity as well as air temperature. The application of ARIMA (Autoregressive Integrated Moving Average) and multi input transfer function was intended to model the rainfall which would be forecasted based on the best model chosen. There were two kinds of variables used in this study. Those were rainfall as the output series while humidity and air temperature as the input series during January 2009 to October 2014. The result showed that ARIMA ([3], 1, [12]) had a fewer Schwart’z Bayesian Criterion (SBC) value 293.199 than multi input transfer function model (0,0,0) (0,1,0) with the result 906.9632.
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