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The Clustering of Paddy Fields Using Machine Learning Algorithms in the Province of South Sumatera

机译:南苏马特省利用机器学习算法的稻田的聚类

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In this paper, we were clustering paddy fields in the province of South Sumatera using machine learning algorithms. We chose machine learning algorithms because this algorithm is very relevant to the problem to be studied. The contribution of this study is in the form of result from the clustering of paddy fields which used as input or consideration for the government in determining policies related to the farming area. Policies that can use the results of the clustering of paddy fields include determining the most appropriate area for expanding paddy fields in the province of South Sumatera. The results of clustering using machine learning techniques show the expansion of paddy fields could be done in 13 districts or as much as 76.4% of the total districts in the province of South Sumatera.
机译:在本文中,我们使用机器学习算法在南萨默马省的聚类稻田。 我们选择了机器学习算法,因为该算法与要研究的问题非常相关。 本研究的贡献是稻田集群的结果,该领域用作政府在确定与农业区域有关的政策时的投入或考虑。 可以使用稻田集群的结果的策略包括确定南苏拉州省内扩展稻田的最合适的区域。 使用机器学习技术的聚类结果表明,稻田的扩展可以在13个地区或南·萨姆帕特省的总区的76.4%。

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