DOI: https://doi.org/10.14710/medstat.13.1.25-35

INTERPOLASI KRIGING DALAM PEMODELAN GSTAR-SUR DAN GSTARX-SUR PADA SERANGAN HAMA PENGGEREK BUAH KOPI

Henny Pramoedyo  -  Jurusan Statistika, Fakultas MIPA, Universitas Brawijaya, Indonesia
*Arif Ashari  -  Jurusan Statistika, Fakultas MIPA, Universitas Brawijaya, Indonesia
Alfi Fadliana  -  Jurusan Statistika, Fakultas MIPA, Universitas Brawijaya, Indonesia
Open Access Copyright (c) 2020 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

How to cite (APA): Pramoedyo, H., Ashari, A., & Fadliana, A. (2020). INTERPOLASI KRIGING DALAM PEMODELAN GSTAR-SUR DAN GSTARX-SUR PADA SERANGAN HAMA PENGGEREK BUAH KOPI. MEDIA STATISTIKA, 13(1), 25-35. https://doi.org/10.14710/medstat.13.1.25-35
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Abstract
The GSTAR and GSTARX models normally can only be formed from observed locations. The problem that sometimes occurs is that not all locations that want to be modeled have complete data as well as other locations. This study uses GSTAR and GSTARX modeling using SUR approach and combines them with the kriging interpolation technique for forecasting coffee berry borer attack in Probolinggo Regency. This modeling is called GSTAR-SUR Kriging and GSTARX-SUR Kriging. This study aims to determine the best model between GSTAR-SUR Kriging and GSTARX-SUR Kriging for forecasting coffee borer attack in an unobserved location. The result of this study shows that GSTAR-SUR Kriging and GSTARX-SUR Kriging models can be used for forecasting coffee berry borer attack in unobserved locations with high forecast accuracy shown by MAPE values <10%. In this study the GSTARX-SUR Kriging model (1,[1,12])(10,0,0) is the best model for forecasting boffee berry borer attacks in unobserved locations.

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Keywords: GSTAR; GSTARX; Forecasting; Kriging Interpolation; Coffee Berry Borer

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