Analisis Dampak Iklim Terhadap Produktivitas Tanaman Pangan dengan Model VAR dan GLM
DOI:
https://doi.org/10.46880/tamika.Vol4No2(SEMNASTIK).pp56-63Keywords:
Climate Variables, Food Crop, Vector Autoregression (VAR), Generalized Linear Model (GLM)Abstract
Food crops are essential for ensuring food security and combating hunger. Climate change has emerged as a significant obstacle that is impacting the long-term viability of the agricultural industry, particularly in relation to food crops. The objective of this study is to examine the influence of climate conditions on the efficiency of food crop production in Sumatra. This will be accomplished through the utilization of VAR and GLM models, in addition to the OSEMN framework. The VAR model study shows that wind speed has a statistically significant influence on peanut production (p-value 0.000563). Similarly, the GLM model analysis reveals that wind speed has a statistically significant impact on rice (p-value 0.00095) and maize (p-value 0.000686) productivity. Based on the MAPE metric, the GLM model demonstrates superior performance compared to the VAR model in accurately predicting soybean production with an accuracy rate of 9.05% and peanut productivity with an accuracy rate of 8.84%. This study aims to provide assistance in reducing the effects of climate change and adapting to them in the agricultural industry, while also improving the production of food crops.
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Copyright (c) 2024 Fitria Kadir, Roni Yunis
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