KERNEL NONPARAMETRIC REGRESSION FOR THE MODELIZING OF THE PRODUCTIVITY WETLAND PADDY

Tiani Wahyu Utami, Martyana Prihaswati, Vega Zayu Varima

Abstract


Nonparametric regression can be used when the relationship between the response variable and the predictor
variables have an unknown pattern form the regression curve. One of the method that can be used to predict
productivity of the wetland paddy is a nonparametric regression kernel. In kernel regression, there are several
types of estimator that can be used to modelling productivity of wetland paddy in Central Java, one of which is
Nadaraya-Watson estimator. Variables used in the study of the productivity of rice as the response variable,
while the predictor variables that harvested area, production and rainfall. Based on estimates indicate that the
kernel nonparametric regression optimum bandwidth value 1.2 and GCV = 1.7577. The coefficient of
determination (R
2
) of 94.23% and MSE of 0.8560.
 
Keywords: Kernel Nonparametric Regression, Productivity, Wetland Paddy

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