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ITS » Paper and Presentation » Statistika - S2
Posted by fandikaaqsa@its.ac.id at 04/03/2016 14:30:31  •  808 Views


PEMODELAN JUMLAH HARI HUJAN PER BULAN DI KABUPATEN INDRAMAYU DENGAN PENDEKATAN ZERO INFLATED MODEL ZIM

THE MODELING OF NUMBER OF MONTHLY RAINY DAYS IN INDRAMAYU REGENCY USING ZERO INFLATED MODEL ZIM APPROACH

Author :
DAMANIK, FRITS FAHRIDWS ( 1312201716 )




ABSTRAK

Produktivitas pertanian secara umum dipengaruhi oleh faktor genetis jenis bibit dan faktor lingkungan seperti jenis tanah pengelolaan lahan teknologi dan iklimcuaca. Dari faktor lingkungan keadaan cuaca sangat memegang peranan penting terhadap keberhasilan pertanian. Kondisi ini terjadi tidak lepas dari sangat berfluktuatifnya kejadian hujan antar waktu sehingga pembudidayaan tanaman perlu disesuaikan terhadap fluktuasi curah hujan dan frekuensi hujan. Untuk antisipasi terhadap perubahan curah hujan dan frekuensi hujan yang tiba-tiba ekstrim diperlukan suatu sistem peringatan dini dengan memanfaatkan model prediksi jumlah hari hujan sehingga gambaran frekuensi hujan beberapa periode ke depan dapat di peroleh lebih awal. Pemodelan terhadap kasus kejadian diskrit secara seriesseperti jumlah hari hujan per bulandapat dilakukan dengan menggunakan metode Zero Inflated Model ZIM yang dapat mengakomodir banyaknya nilai pengamatan bernilai nol excess zeros dalam deret data series. Penelitian ini menggunakan data jumlah hari hujan di Kabupaten Indramayu pada periode 1965-2010 dimana sebanyak 1830 persen dari data merupakan observasi bernilai nol. Hasil penelitian memperlihatkan bahwa model Negative Binomial NBautoregression adalah model terbaik yang dihasilkan pendekatan ZIM dengan nilai AIC terkecil yaitu sebesar 3.067544. Model ini juga memberikan nilai MSE yang jauh lebih kecil yaitu sebesar 12334dibandingkan dengan MSE yang dihasilkan dengan menggunakan pendekatan ARIMA yaitu sebesar 499424.


ABSTRACT

Generally agricultural productivity was not only influenced by genetic factor kinds of seeds but also environmental factor such as kinds of soil land management technology and climate. Among various environmental factor weather situation plays important role on determining agricultural success. Such condition could not separate from the rainfall and its frequency that fluctuate in occurrence. Thus an early warning system is needed for anticipating a sudden or extreme change on rainfall and its frequency. Some early warning system of rainfall is built by utilizing model of number of rainy days to predict further condition. This research aims to build a model of the number of monthly rainy days in Indramayu Regency using the data series from 1965 to 2010. We found that the case is occurs on discrete pattern and its data have 1830 percent observations that contain zero. Thus we use Zero Inflated Model ZIM method to build a monthly rainy days model because its ability to accommodate the excess zero effect. The results shows that the Negative Binomial NB autoregression was the finest model produced using ZIM approach. It resulting AIC value of 3.067544 and MSE 12334. Such value is smaller compared to the model produced using ARIMA approach.



Keywordspoison regreision model; Negatif binomial regreision model; Zero-Inflated model; Excess zero; Rainfall forecasting; ARIMA
 
Subject:  Analisis regresi
Contributor
  1. Dr. rer. pol. Heri Kuswanto, M.Si
Date Create: 04/03/2016
Type: Text
Format: PDF
Language: Indonesian
Identifier: ITS-paper-13121150008602
Collection ID: 13121150008602
Call Number: RTSt 519.536 Dam p


Source
Paper and Presentations of Statistics, RTSt 519.536 Dam p, 2014

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Copyright @2016 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




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