Application Of The C4.5 Algorithm To Determining Student's Level Of Understanding

Adeita A. Ndraha, Jaya Tata Hardinata, Y. Purba
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Abstract

This research was conducted to find the rules of the model in measuring the level of students' understanding of the subject. During this pandemic, the learning process is carried out online, so it is difficult to measure students' ability to master the material. This measurement needs to be done so that the evaluation process can be carried out so that the ability of students in one group to achieve the target level of understanding. Currently, evaluation activities have never been carried out because they do not have a model so that evaluation can only be done by giving quizzes and exercises. This problem can be solved by using data mining algorithm C4.5. Attributes used as parameters for assessing student understanding of lessons such as Teaching Method (C1), Learning Media (C2), Communication (C3), Experience (C4), Teaching Materials/Modules/Assignments (C5), Learning Duration (C6). The six attributes are used to find the relationship between each other that influence each other to get the highest root so that a decision tree will be obtained that produces the rules of the relationship between each attribute in determining student understanding of the subject. This rule or rule will be used as the basis for making an information system so that it can be applied to end users, namely schools.
C4.5算法在确定学生理解水平中的应用
本研究旨在发现该模型在衡量学生对学科的理解水平方面的规律。在这次疫情期间,学习过程是在线进行的,因此很难衡量学生掌握材料的能力。需要进行这种测量,以便进行评估过程,以便一组学生的理解能力达到目标水平。目前,评价活动从未开展过,因为没有一个模式,只能通过小测验和练习来进行评价。这个问题可以通过使用数据挖掘算法C4.5来解决。作为评估学生对课程理解的参数的属性,如教学方法(C1)、学习媒介(C2)、交流(C3)、经验(C4)、教材/模块/作业(C5)、学习时长(C6)。利用这6个属性寻找相互影响的关系,求出最高根,从而得到一棵决策树,该决策树产生了决定学生对学科理解的各个属性之间关系的规则。该规则或规则将被用作制作信息系统的基础,以便它可以应用于最终用户,即学校。
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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