基于k近邻(KNN)的BAZNAS网站人工智能方法

Y. Sari, M. Maulida, Endi Gunawan, J. Wahyudi
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引用次数: 5

摘要

阿米尔天课国家机构(BAZNAS)是一个分发天课的国家机构。作为伊斯兰教的主要基础之一,天课显然是非常重要的。但是,受援国的资料往往不清楚,从而造成公平分配天课方面的问题。本研究试图提供一个解决方案,通过使用k -最近邻方法,将BAZNAS网站上的天课接受者分为两类:贫困和贫困。本研究得出,分别使用分类报告、混淆矩阵和ROC-AUC的KNN方法准确率分别为97%、96.7%和97.7%
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Artificial Intelligence Approach For BAZNAS Website Using K-Nearest Neighbor (KNN)
Amil Zakat National Agency (BAZNAS) is a national institution for the distribution of zakat. As one of the main foundations in Islam, zakat is, obviously, very important to be fulfilled. However, it is very often that the data of the recipient became unclear that it caused problems in terms of a fair distribution of zakat. This research tried to offer a solution by doing a classification of the recipient of zakat on the BAZNAS websites into two categories: indigent and poor, using K-Nearest Neighbor method. This research concluded that the accuracy of KNN method by using classification report, confusion matrix, and ROC-AUC respectively resulted in accuracy of 97%, 96.7%, and 97.7%
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