K-Means聚类模型提高文凭专业毕业生能力

Q3 Social Sciences
H. Prasetyo, Wawa Wikusna, Ferra Arik Tridalestari
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引用次数: 0

摘要

学生完成学业是大学学习过程的结果。与这种情况有关的问题是,许多文凭学生往往在完成学业时迟到,甚至辍学。在根据掌握的能力预测学生毕业率方面,大学各系没有一个重要的衡量工具。本文提出了一个程序模型来预测信息系统文凭课程学生的基本能力,将其映射到能力水平中,以减少学习过程中的延迟。程序模型中使用的方法是采用K-Means聚类模型方法的定量方法。结果表明,信息系统文凭课程的及时毕业率显著提高。关键词:毕业生能力,文凭课程学生,信息系统,K-Means聚类,高等教育;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
K-Means clustering model to improve competency of diploma program graduates
Completion of studies by students is the result of the process carried out in the learning process in university. The problem that arises related to this condition is that many diploma students are often late in completing their studies or even dropping out of school. Departments at the university do not have a significant measuring tool in predicting student graduation rates based on the competencies mastered. This paper proposes a program model to predict the basic abilities of Information System Diploma Program students to be mapped in the level of ability in an effort to reduce the delay in the learning process. The method used in the program model was a quantitative method with a K-Means Clustering model approach. The results showed that there was a significant increase in the timely graduation rate for Information System Diploma Program. Keywords: Graduates Competency, Diploma Program Student, Information System, K-Means Clustering, Higher Education;
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来源期刊
Cypriot Journal of Educational Sciences
Cypriot Journal of Educational Sciences Social Sciences-Education
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