Open AccessApplication of GSTAR kriging model in forecasting and mapping coffee berry borer attack in Probolinggo district
Author(s) -
Henny Pramoedyo,
Arif Ashari,
Alfi Fadliana
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1563/1/012005
Subject(s) - kriging , autoregressive model , interpolation (computer graphics) , mathematics , statistics , computer science , artificial intelligence , motion (physics)
Generalized Space Time Autoregressive (GSTAR) is one of multivariate time series modeling that considers aspects of location with heterogeneous location characteristics. The GSTAR model normally can only be used in forecasting an event in the future at the observed locations. The problem that often occurs in some cases is that there are locations to be modeled that do not have sufficient or incomplete data as data in other locations. For this reason, several alternatives can be done, and one of them is by combining the GSTAR model with the kriging interpolation technique. This modeling is known as GSTAR Kriging modeling. In this research, GSTAR Kriging modeling is applied in predicting and mapping coffee berry borer attacks in Probolinggo District. The model parameters are estimated using the GLS method in the SUR equation system. Forecasting results indicate that the GSTAR Kriging model has a high forecasting accuracy and is not much different from the GSTAR model. Meanwhile, based on the forecasting map, it can be seen that the peak of coffee berry borer attack is predicted to occur in July 2019 with the attack center located in Tiris Sub-district.