西爪哇的社会福利问题群体使用k -均值,而FUZZY c -均值

Lina Rohmaniah, Ahmad Faqih, Tatik Suprapti
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引用次数: 0

摘要

在印度尼西亚的一些省份,包括西爪哇省,社会福利问题仍然存在。社会福利问题不可能完全克服,但根据政策观念,可以减少,因此需要分析。将有社会福利问题的人的数据分组,根据这些数据找出最佳群体,将提供替代政策和适当的方法。本研究的目的是在DBI评价结果的基础上,运用k-均值和模糊c-均值方法寻找社会福利问题的最佳群体。分组方法为k-means和模糊c-means算法方法。从本研究的结果来看,基于最小DBI评价的模糊c-means算法实验中得到的最好的2组,即k-means算法的DBI值为0.029,模糊c-means算法的DBI值为0.006。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENGELOMPOKAN PENYANDANG MASALAH KESEJAHTERAAN SOSIAL DI JAWA BARAT MENGGUNAKAN K-MEANS DAN FUZZY C-MEANS
Social welfare problems still occur in some provinces in Indonesia, including in West Java. Social welfare problems cannot be completely overcome, but according to policy perceptions, they can be reduced, therefore analyses are required. Grouping data on people with social welfare problems to find out the best group based on the data will provide alternative policies and appropriate methods. The purpose of this study was to find the best group of people with social welfare problems using the k-means and fuzzy c-means methods based on the results of the DBI evaluation. The methods used for this grouping were the k-means and fuzzy c-means algorithm methods. From the results of this study, it was obtained the best 2 groups from the experiment of fuzzy c-means algorithms based on the smallest DBI assessment or close to 0 between the k-means and fuzzy c-means algorithms from each DBI value, they  were k-means algorithm with value of 0.029 and fuzzy c-means algorithm with value of 0.006.  
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