Department of Mathematics, Faculty of Science and Technology Universitas Jambi
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en
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A serious problem that impacts the agricultural sector is climate change. One of the impacts is reduced productivity of food crops such as rice. Climatic factors such as precipitation and the frequency of rainy days play a crucial role in agricultural production. Utilization of Lowland Swamps as agricultural land has great potential to increase rice productivity. The research aims to illustrate the characteristics of rice productivity in the Lowland Swamp area of Hulu Sungai Utara Regency (HSU) and estimate the parameters in the spatial panel data model affecting it. The study employed panel data spatial regression using the Spatial Autoregressive Model Fixed Effect (SAR-FE) and Spatial Error Model Fixed Effect (SEM-FE) methods. The findings indicated that the rice productivity in the Hulu Sungai Utara (HSU) Regency reached its peak in 2005; conversely, it had a decline and reached its lowest point in 2021. The SAR-FE was selected as the optimal model, with a coefficient of determination of 89,94%. The SAR-FE model demonstrated that rainfall significantly positively affected rice productivity in the Hulu Sungai Utara (HSU) Regency. Simultaneously, rainy days significantly negatively affected the rice productivity of the Hulu Sungai Utara (HSU) Regency.
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