Algoritma Klasifikasi Data Mining Untuk Memprediksi Siswa Dalam Memperoleh Bantuan Dana Pendidikan

Senna Hendrian
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引用次数: 27

Abstract

: Education is one of the components of life that can support the success of a person towards life that much better again. Especially for the children that are in the scope of the age of compulsory education. but not all children can attend compulsory education, because several factors cause, one of which is the issue of tuition fees. To cope with the existing problems, then a standalone compiled Bina Bangsa School programs Help Fund education for students who are considered less capable in economic strata. In this study, the author uses the classification Algorithm Datamining Algorithm C4.5 to predict students in obtaining the help of the Education Fund. Sample data are drawn from the Upper secondary school (HIGH SCHOOL) Self-sustaining Bina Bangsa (BBM) that located in Kecamatan Gunungputri Kab. Bogor. From the results of testing and Validation of tests used Cros Confusion Matrix and ROC Curves. The results obtained for the value of Accuracy Algorithm C 4.5 is 98.80%, a value for the Precision of 98.02%, and the value for Sensitivity or Recall of 99.00%. Thus the algorithm C 4.5 is the best techniques and algorithms to predict Students in obtaining the help of the Education Fund.
数据挖掘分类算法,预测学生获得教育资金援助
当前位置教育是生活的一个组成部分,它可以支持一个人的成功,走向更美好的生活。特别是在义务教育年龄范围内的孩子。但并不是所有的孩子都能接受义务教育,原因有几个,其中之一是学费的问题。为了解决存在的问题,当时一个独立编制的比那邦萨学校项目帮助基金教育那些被认为在经济阶层中能力较弱的学生。在本研究中,作者使用分类算法数据挖掘算法C4.5来预测学生获得教育基金的帮助。样本数据来自位于Kecamatan Gunungputri Kab的高中自持Bina Bangsa (BBM)。茂物。从检验结果和检验验证使用交叉混淆矩阵和ROC曲线。准确度(Accuracy)为98.80%,精密度(Precision)为98.02%,灵敏度或召回率(Recall)为99.00%。因此,c4.5算法是预测学生获得教育基金帮助的最佳技术和算法。
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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