PERBANDINGAN MODEL ARIMA DAN FUNGSI TRANSFER PADA PERAMALAN CURAH HUJAN KABUPATEN WONOSOBO

Main Authors: Hidayah, Siti Lis Ina Atul, Rusgiyono, Agus, Wilandari, Yuciana
Format: Article info application/pdf Journal
Bahasa: eng
Terbitan: Departemen Statistika FSM Undip , 2015
Subjects:
Online Access: https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10239
https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10239/9941
ctrlnum article-10239
fullrecord <?xml version="1.0"?> <dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><title lang="en-US">PERBANDINGAN MODEL ARIMA DAN FUNGSI TRANSFER PADA PERAMALAN CURAH HUJAN KABUPATEN WONOSOBO</title><creator>Hidayah, Siti Lis Ina Atul</creator><creator>Rusgiyono, Agus</creator><creator>Wilandari, Yuciana</creator><subject lang="en-US">Rainfall, ARIMA, Transfer Function</subject><description lang="en-US">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.&#xA0; 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&#x2019;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</description><publisher lang="en-US">Departemen Statistika FSM Undip</publisher><contributor lang="en-US"/><date>2015-10-30</date><type>Journal:Article</type><type>Other:info:eu-repo/semantics/publishedVersion</type><type>Journal:Article</type><type>File:application/pdf</type><identifier>https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10239</identifier><source lang="en-US">Jurnal Gaussian; Vol 4, No 4 (2015): Jurnal Gaussian; 1037-1044</source><source>2339-2541</source><language>eng</language><relation>https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10239/9941</relation><recordID>article-10239</recordID></dc>
language eng
format Journal:Article
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author Hidayah, Siti Lis Ina Atul
Rusgiyono, Agus
Wilandari, Yuciana
title PERBANDINGAN MODEL ARIMA DAN FUNGSI TRANSFER PADA PERAMALAN CURAH HUJAN KABUPATEN WONOSOBO
publisher Departemen Statistika FSM Undip
publishDate 2015
topic Rainfall
ARIMA
Transfer Function
url https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10239
https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10239/9941
contents 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
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Statistics
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