使用最大依赖属性对学生成绩数据集进行属性选择

Rd. Rohmat Saedudin, E. Sutoyo, S. Kasim, Hairulnizan Mahdin, I. R. Yanto
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引用次数: 12

摘要

作为一所高等教育机构,了解哪一个学期的GPA对学生的学习成绩影响最大是很重要的,但也是很有挑战性的。因此,本文考虑使用基于粗糙集理论的最大依赖属性(MDA)。数据集取自电信大学信息系统理事会(SISFO)。结果表明,最具决定性的属性是第2绩点,其次是第3绩点、高考绩点、第1绩点、学业能力测试绩点和第4绩点。通过早期了解m分数的最决定性属性,可以在机构学术研究期间制定精心策划的战略方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Attribute selection on student performance dataset using maximum dependency attribute
As a higher education institution, knowing which GPA of the semester has the most determinant to affecting the academic performance of students is important yet challenging. Therefore, this paper deliberates the usage of rough set theory based Maximum Dependency Attributes (MDA). The dataset is taken from the Directorate of Information Systems (SISFO), Telkom University. The result showed that the most determinant attribute is 2th GPA, followed with 3rd GPA, Entrance Examination, 1st GPA, Academic Aptitude Test, and 4th GPA, respectively. By early knowing the most determinant attribute in which score of the m, a well-planned strategic program can be set during the institution academic study period.
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