Rainfall model on area of rice production in Sragen, Karanganyar and Klaten by using Generalized Space Time Autoregressive (GSTAR)

International Conference on Mathematics: Education, Theory and Application

数学;教育

Handajani, S.S.^1 ; Pratiwi, H.^1 ; Susanti, Y.^1 ; Subanti, S.^1 ; Respatiwulan^1 ; Hartatik^2

Statistics Department of Mathematics and Natural Sciences, Faculty of Sebelas, Maret University, Indonesia^1

Informatics of Mathematics and Natural Sciences, Faculty of Sebelas, Maret University, Indonesia^2

关键词: Fluctuation conditions;    Food insecurity;    Least square methods;    Normalized cross correlation;    Planting period;    Rainfall prediction;    Rice production;    Stepwise procedure;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/855/1/012015/pdf
DOI  :  10.1088/1742-6596/855/1/012015

学科分类：发展心理学和教育心理学

来源: IOP

【 摘 要 】

The planning of planting period became non-optimal due to the uncertain rainfall fluctuation condition in the past few years. To anticipate food insecurity caused by such a matter, the development of rainfall prediction models in several rice production areas in Central Java, which represent the center for rice production, is required. This paper provides the application of GSTAR model on the rainfall data in Sragen Regency, Karanganyar Regency, and Klaten Regency with considering time and location conditions. The weighting applied in the model was normalized cross-correlation. By applying the least square method and stepwise procedure, GSTAR model for six, seven in Sragen, seven areas in Karanganyar, and seven areas in Klaten respectively was obtained. The validity of the model was tested by applying RMSE.