2015年中使用自组织映射算法(SOM)分析贫困和经济不平等因素的小组

Siti Isnaeni
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引用次数: 1

摘要

贫穷问题仍然是印度尼西亚作为一个国家的整个历史上的一个主要问题。印度尼西亚各地区穷人的分布也不均衡。在贫困理论中提到,影响贫困问题出现的因素源于经济方面的限制,无论是物质资本(收入)还是人力资本。因此,需要以减贫目标为导向的规划,使减贫和经济差距能够通过目标实现。本研究旨在通过应用数据挖掘算法确定2015年中爪哇贫困和经济差距分组,分析影响贫困和经济不平等的因素,了解其特征。在贫困因素分组中,将使用的研究对象是影响贫困和经济差距的变量。分组分析采用数据挖掘方法,采用Kansans和Kohonen自组织地图(SOM)算法。基于WCSS图和聚类号验证的分析结果确定为聚类5,其中三宝垄市为聚类1,Kudus在聚类2,聚类3包含5个城市,聚类4包含6个区,聚类5包含22个区。关键词:贫困,经济差距,聚类K-means,自组织地图(SOM),中爪哇
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANALISIS KELOMPOK FAKTOR-FAKTOR KEMISKINAN DAN KESENJANGAN PEREKONOMIAN MENGGUNAKAN ALGORITMA SELF ORGANIZING MAPS (SOM) DI JAWA TENGAH TAHUN 2015
The problem of poverty continues to be a major problem throughout Indonesia's history as a State. The distribution of the poor is also uneven in all regions in Indonesia. In the theory of poverty mentioned that the factors that influence the emergence of poverty problems originated from limitations in terms of economic, whether physical capital (income) or human capital. Therefore, poverty reduction target oriented planning is needed, so that the poverty reduction and economic disparity can be achieved by target. This study aims to analyze the factors that affect poverty and economic inequality to know the characteristics by applying data mining algorithms to determine the grouping of poverty and economic disparities in Central Java in 2015. In the grouping of poverty factors, the object of research that will be used are variables affecting poverty and economic disparity.The group analysis used data mining approach with Kansans and Kohonen Self Organizing Maps (SOM) algorithm.The result of analysis based on WCSS graph and cluster number validation is determined by cluster number 5 with Semarang City as cluster 1, Kudus is in cluster 2, cluster 3 contains 5 cities, in cluster 4 containing 6 districts and 22 other districts are in cluster 5. Keywords: Poverty, Economic Gap, Clustering K-means, Self Organizing Maps (SOM),central java.
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