基于农业部门收入的西爪哇省Kab分类决策树算法

Amril Mutoi Siregar, A. Fauzi
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引用次数: 2

摘要

农村社区的福利水平,特别是西爪哇省,特别是那些远离城市的人,离不开农业部门的主要收入。农业涵盖了许多行业,仍然有许多生活在贫困线以下的人。因为地方政府提供的设施和资金仍然很少。给出的问题根源在于,几乎所有的城辖区村庄都没有正确的数据,准确而精准地了解问题所在的状况和潜力所在的村庄。这项研究预计将是错误的方式来了解未来的发展机会,通过分析来自农业部门的收入数据,以更好地决策。这种数据处理技术可以植入当地政府,用于衡量其农业的成功。本研究的特征选择是使用决策树算法对数据进行自动分类。经过研究,获得了90%的准确率。关键词:数据挖掘,分类,决策树,农业
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Klasifikasi Kab Kota Provinsi Jawa Barat Berdasarkan Pendapatan Dari Sektor Pertanian Dengan Algoritma Decision Tree
The welfare level of rural communities, especially the province of West Java, especially those living away from the cities, can not be separated from the primary revenue is in the agriculture sector. The agricultural industry covers many industries and still many lives under the poverty line. Because facilities and financing are still minimal from the local government. Given the root of the problem is that almost all villages in the city district do not have the correct data, accurate and precise about the condition of the issues and potential of the village-owned. This research is expected to be the wrong way to know the future development opportunities by analyzing the revenue data from the agriculture sector to better decision making. And this data processing technique can be implanted for the local government to measure the success of its agriculture. The selection of features in this study is to use the Decision Tree algorithm to classify data automatically. After this research, the Accuracy of 90% obtained.Keywords: DataMining, classification, Decision Tree, agriculture
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