Analisis Perbandingan Metode Fuzzy Logic Dan Metode SAW Dalam Pemilihan Keluarga Penerima Bantuan Sosial

Siti Ma'rifatul Latifah, Dwi Agus Diartono
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Abstract

Ensuring and fulfilling the needs of the community isa form of government responsibility to reduce existing socialinequalities. One of the efforts that the government has made isto provide social assistance through the Non-Cash FoodAssistance program. However, the process of selecting recipientsof social assistance is often not on target. For this reason, it isnecessary to build a system that is able to support in determiningdecisions for the selection of families receiving social assistance.To help the selection process of social assistance recipients, ofcourse, it must use the right and appropriate method so that theselection process produces social assistance recipients who reallydeserve assistance. The selection process in this study uses twodecision support methods, namely Fuzzy Logic and SimpleAdditive Weighting (SAW) and has conducted accuracy tests onboth methods against the suitability of recipient eligibility data,so that it can be seen which method has the highest level ofaccuracy in the selection of social assistance recipients. Theresults of the accuracy test carried out in this study are that bothmethods produce the same high level of accuracy in thesuitability of prospective recipient eligibility results, namely100%, this means that both methods can be used in determiningrecipients of social assistanc.
模糊逻辑法和 SAW 法在选择接受社会援助家庭中的比较分析
确保并满足社区的需求是政府减少现有社会不平等的一种责任。政府所做的努力之一就是通过非现金食品援助计划提供社会援助。然而,选择社会援助对象的过程往往不尽人意。因此,有必要建立一个系统来帮助决定如何选择接受社会救助的家庭。当然,要帮助选择社会救助对象,就必须使用正确和适当的方法,使这些选择过程产生出真正值得救助的社会救助对象。本研究中的选择过程使用了两种决策支持方法,即模糊逻辑法和简单加权法(SAW),并针对受助人资格数据的适用性对两种方法进行了准确性测试,以了解哪种方法在选择社会救助对象时准确性最高。本研究进行的准确性测试结果表明,两种方法在预期受助人资格结果的适用性方面都能产生同样高的准确性,即 100%,这意味着这两种方法都可用于确定社会援助受助人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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