受援国利用天真贝斯的方法确定了穷人的可行性(案例研究:北方采集区)

Nur Madia, Anindita Septiarini, H. Hatta, Hamdani Hamdani, Masna Wati
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引用次数: 0

摘要

贫困是指无法满足生活必需品,如食物、衣服和住所。穷人的平均月人均支出低于贫困线。印度尼西亚的贫困问题仍未得到解决;政府继续努力为整个社会提供最好的服务,以便贫穷问题至少能够继续减少。政府关心穷人的一种形式是向穷人提供援助计划。本研究将根据从国家社会经济调查(Susenas)结果中获得的北Penajam Paser (PPU)社区的数据进行分类,以了解Naïve贝叶斯方法如何确定贫困受援者的资格。在已有研究的基础上,生成了贫困受援者的确定系统,其中测试结果在第三种场景下准确率最高,即60%或328个培训数据,40%或218个测试数据,准确率为77.98%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Penentuan Kelayakan Masyarakat Miskin Penerima Bantuan Menggunakan Metode Naïve Bayes (Studi Kasus: Kabupaten Penajam Paser Utara)
Contents Poverty is the inability to meet the necessities of life, such as food, clothing, and shelter. The poor have an average monthly per capita expenditure below the poverty line. The case of poverty in Indonesia is still unresolved; the Government continues to try to give the best to the entire community so that the problem of poverty can at least continue to decrease. One form of government concern for the poor is the assistance program provided to the poor. This study will classify based on data from the North Penajam Paser (PPU) community obtained from the results of the National Socio-Economic Survey (Susenas) to know how the Naïve Bayes method is in determining the eligibility of the poor recipients of assistance. Based on the research that has been carried out, a system for determining the poor recipients of assistance is produced, where the test results get the highest accuracy in the third scenario, namely 60% or 328 training data and 40% or 218 test data, where the accuracy obtained is 77.98%.
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