THE RAINFALL PREDICTION AS A BASE OF PLANNING THE RICE AND CROPS PLANTING SYSTEM USE GENERAL REGRESSION NEURAL NETWORK MODEL

Warsito, Budi and Tarno, Tarno and SUGIHARTO, ARIS (2008) THE RAINFALL PREDICTION AS A BASE OF PLANNING THE RICE AND CROPS PLANTING SYSTEM USE GENERAL REGRESSION NEURAL NETWORK MODEL. Project Report. Lembaga Penelitian Undip, Undip. (Unpublished)

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Official URL: http://stat.undip.ac.id

Abstract

This paper discuss about General Regression Neural Network (GRNN) modelling to the rainfall data at some territory in the Central Java that dependent on rainfall for irrigation in the planting system i.e Musuk, Ngaringan and Jakenan. The data that used are the dasarian data (the every ten day) while the input model are choosen from ARIMA model with the ACF and PACF plot. The result of predict in sample show that GRNN model have a high precision, although the predict out of sample is guaranted better than ARIMA not yet. Then the model is used to forecast some next stage. The result of rainfall forecasting conclude that each territory is better to apply the rice-crops-crops in the planting system, with consider the estimation of climate anomaly to begins the planting time. Key Words : GRNN, ARIMA, rainfall, planting system

Item Type:Monograph (Project Report)
Subjects:Q Science > Q Science (General)
Divisions:Faculty of Science and Mathematics > Department of Statistics
ID Code:3523
Deposited By:Mr Hasbi Yasin
Deposited On:13 Jan 2010 15:24
Last Modified:13 Jan 2010 15:24

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