Repo Dosen ULM

Modelling and predicting wetland rice production using support vector regression

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dc.contributor.author Alkaff, Muhammad
dc.contributor.author Khatimi, Husnul
dc.contributor.author Puspita, Wenny
dc.contributor.author Sari, Yuslena
dc.date.accessioned 2023-04-28T11:29:15Z
dc.date.available 2023-04-28T11:29:15Z
dc.date.issued 2019-04-01
dc.identifier.issn 1693-6930
dc.identifier.uri https://repo-dosen.ulm.ac.id//handle/123456789/29941
dc.description.abstract Food security is still one of the main issues faced by Indonesia due to its large population. Rice as a staple food in Indonesia has experienced a decline in production caused by unpredictable climate change. In dealing with climate change, adaptation to fluctuating rice productivity must be made. This study aims to build a prediction model of wetland rice production on climate change in South Kalimantan Province which is one of the national rice granary province and the number one rice producer in Kalimantan Island. This study uses monthly climatic data from Syamsudin Noor Meteorological Station and quarterly wetland rice production data from Central Bureau of Statistics of South Kalimantan. In this research, Support Vector Regression (SVR) method is used to model the effect of climate change on wetland rice production in South Kalimantan. The model is then used to predict the amount of wetland rice production in South Kalimantan. The results showed that the prediction model with the RBF kernel with the parameter of C=1.0, epsilon=0.002 and gamma=0.2 produces good results with the RMSE value of 0.1392. en_US
dc.language.iso en_US en_US
dc.publisher TELKOMNIKA en_US
dc.relation.ispartofseries 17;2
dc.subject Indonesia, prediction, support vector regression, wetland rice en_US
dc.title Modelling and predicting wetland rice production using support vector regression en_US
dc.type Article en_US


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