基于粗糙回归模型的优势标准及其影响学生学习成绩的因素

R. Efendi, N. Yanti, A. Wenda, Susnaningsih Mu’at, N. Samsudin, M. M. Deris
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引用次数: 3

摘要

普通最小二乘模型被广泛用于估计影响学生成绩的重要因素。有些因素是定性的,使用标准或类别进行测量。然而,影响学生累积平均绩点的各个因素的决定性标准无法通过该模型确定。在本文中,我们感兴趣的是建立一个基于依赖属性泛化的粗糙回归模型来确定各因素的主导准则的新过程。基于结果,所提出的程序能够调查影响学生成绩的主导标准和因素,例如,以主导标准使用的语言是“多-多”,以主导标准使用的FB朋友是“多”,以主导标准使用的快餐是“从不”。这个建议的程序非常适合用于处理分类数据。
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Dominant Criteria and Its Factor Affecting Student Achievement Based on Rough-Regression Model
the ordinary least square model has been widely considered to estimate the significant factors which influence the student achievement. Some factor is qualitative type and measured using criteria or categories. However, the decisive criteria for each factor which affect to the cumulative grade point average of student cannot be determined by this model. In this paper, we are interested to build a new procedure using rough-regression model in determining the dominant criteria from each factor based on generalization of dependency attribute. Based on result, the proposed procedure is capable to investigate the dominant criteria and factors affecting student achievement, such as, language spoken with dominant criteria is “many-many”, FB friend with dominant criteria is “many” and fast food with dominant criteria is “never”. This proposed procedure is very appropriate to implement for handling categorical data.
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