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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi
Hartawati, Hartawati
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Mathematics

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Cross-Covariance Weight of GSTAR-SUR Model for Rainfall Forecasting in Agricultural Areas Sulistyono, Agus Dwi; Hartawati, Hartawati; Suryawardhani, Ni Wayan; Iriany, Atiek; Iriany, Aniek
CAUCHY Vol 6, No 2 (2020): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1009.782 KB) | DOI: 10.18860/ca.v6i2.7544

Abstract

The use of location weights on the formation of the spatio-temporal  model contributes to the accuracy of the model formed. The location weights that are often used include uniform location weight, inverse distance, and cross-correlation normalization. The weight of the location considers the proximity between locations. For data that has a high level of variability, the use of the location weights mentioned above is less relevant. This research was conducted with the aim of obtaining a weighting method that is more suitable for data with high variability. This research was conducted using secondary data derived from 10 daily rainfall data obtained from BMKG Karangploso. The data period used was January 2008 to December 2018. The points of the rain posts studied included the rain post of the Blimbing, Karangploso, Singosari, Dau, and Wagir regions. Based on the results of the research forecasting model obtained is the GSTAR ((1), 1,2,3,12,36) -SUR model. The cross-covariance model produces a better level of accuracy in terms of lower RMSE values and higher R2 values, especially for Karangploso, Dau, and Wagir areas.
Co-Authors Agus Dwi Sulistyono, Agus Dwi Aniek Iriany Atiek Iriany Suryawardhani, Ni Wayan