Prediction of Student Graduation Time Using the Best Algorithm

V. Riyanto, A. Hamid, Ridwansyah Ridwansyah
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引用次数: 14

Abstract

Data mining has a very important role in the world of education can help education institutions in predicting and making decisions related to student academic status. We use the NN, SVM and DT algorithms to predict the graduation time of academic students at one of the private universities in Indonesia. The results of this study indicate that the three models produce the accuracy of more than 80%, and the SVM model has an accuracy of 85.18% higher than the other two models. The results arising from this study provide important reference material for planning the future success of students and faculty in early warning to students in the future.
用最优算法预测学生毕业时间
数据挖掘在教育领域有着非常重要的作用,它可以帮助教育机构预测和制定与学生学业状况相关的决策。我们使用神经网络、支持向量机和DT算法来预测印度尼西亚一所私立大学的学生毕业时间。研究结果表明,三种模型的准确率均在80%以上,其中SVM模型的准确率比其他两种模型高85.18%。本研究的结果为学生未来的成功规划和教师对学生未来的早期预警提供了重要的参考资料。
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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