Klasifikasi Kelayakan Penerima PPKS Usulan BPNT dan PHK Lanjut Usia Non Tunai menggunakan Algoritma Cart di Kabupaten Seruyan

Nurahman Nurahman, Aida Puspita Sari, Karina Indah Deswanti
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Abstract

The purpose of this research is to classify the eligibility of recipients of Non-Cash Food Assistance (BPNT) and recipients of the Prosperous Family Program (PPKS) and (PHK) for the elderly proposed in Seruyan District using the CART (Classification and Regression Tree). Algorithm The purpose of the Living Allowance is to assist those in need in meeting their food and welfare needs, especially for underprivileged and elderly families. The research data was obtained through a direct survey of potential beneficiaries in Seruyan District. The data is then processed in the preprocessing stage to ensure good data quality before being used to develop the CART model. The CART model development stage is carried out by dividing the data into two parts, namely. training data and test data, to train and test model performance. The estimation results of the CART model show an accuracy of 87.50%, Precision of 87.50%, and Sensitivity or Recal of 100.00%. Analyzing the results revealed that socioeconomic factors such as family income, employment status, and housing conditions had a significant impact on beneficiary eligibility. These findings provide valuable information for improving social assistance distribution policies in Seruyan District so that assistance is more targeted and maximizes benefits for beneficiary communities. This study is expected to increase the effectiveness and efficiency of the distribution of income assistance and improve the quality of life of beneficiary communities. However, this research has limitations because it was only conducted in one district, so further research is needed with a more representative sample to ensure validity and wider application.
使用购物车算法对塞鲁扬行政区拟议的 BPNT 和非现金老年人公共保健补助金领取者的资格进行分类
本研究的目的是利用 CART(分类与回归树)对塞鲁扬区提出的非现金食品援助(BPNT)受助人、繁荣家庭计划(PPKS)受助人和老年人生活津贴(PHK)受助人的资格进行分类。算法 生活津贴的目的是帮助有需要的人满足其食品和福利需求,尤其是贫困家庭和老年家庭。研究数据是通过对 Seruyan 地区的潜在受益人进行直接调查获得的。然后在预处理阶段对数据进行处理,以确保良好的数据质量,然后再用于开发 CART 模型。CART 模型开发阶段将数据分为两部分,即训练数据和测试数据,以训练和测试模型性能。CART 模型的估计结果显示,准确率为 87.50%,精确率为 87.50%,灵敏度或 Recal 为 100.00%。分析结果显示,家庭收入、就业状况和住房条件等社会经济因素对受益人资格有显著影响。这些研究结果为改善塞鲁扬地区的社会援助分配政策提供了宝贵的信息,从而使援助更有针对性,并使受益社区的利益最大化。这项研究有望提高收入援助分配的有效性和效率,改善受益社区的生活质量。然而,本研究也存在局限性,因为它仅在一个地区进行,因此需要对更具代表性的样本进行进一步研究,以确保研究的有效性和更广泛的应用。
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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