对学生专业数据挖掘技术的应用(SMA PGRI 1 Subang案例研究)

Tubagus Riko Rivanthio, Mardhiya Ramdhani
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引用次数: 1

摘要

SMA PGRI 1苏邦是一所私立学校,它有几个使命,其中一个是建立学术和非学术成果。为了努力完成任务,必须监督学生的成绩。他所做的努力是在根据学生的兴趣和才能选择专业方面提供理解。但在提供理解的活动中,学校还没有一个可以评估学生选择专业的兴趣和才能的模式。该模型可以通过对学生数据的处理得到。数据处理可以使用数据挖掘,即数据挖掘聚类技术来完成。这项技术将为专业的选择提供一种模式。这种聚类过程是基于学生持有的数据的相似性对相似数据进行分组的过程。研究方法采用CRISP-DM方法,分为业务理解、数据理解、数据处理、建模、评估和传播6个阶段。处理的数据为2014年、2015年、2016年班级620个数据。聚类处理结果得到6个聚类,每个聚类具有不同的模型。本研究的结果可以作为学校根据学生的兴趣和才能为学生推荐课程的依据,从而达到学生的最佳学习效果。关键词:聚类,数据挖掘,适用性,专业,学生
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Penerapan Teknik Clustering Data Mining untuk Memprediksi Kesesuaian Jurusan Siswa (Studi Kasus SMA PGRI 1 Subang)
SMA PGRI 1 Subang is a private school that has several missions, one of which is the establishment of academic and non-academic achievements. In an effort to achieve the mission must supervise student achievement. The effort he did was to provide understanding in the selection of majors in accordance with the interests and talents of students. But in the activity of providing understanding, the school does not yet have a model that can evaluate the interests and talents of students to choose majors. The model can be obtained using student data processing. Data processing can be done using data mining, namely data mining clustering techniques. The technique will produce a model in the selection of majors. This clustering process is the process of grouping similar data based on the similarity of data held by students. The research method used is the CRISP-DM method which has 6 stages consisting of: Business Understanding, Data Understanding, Data Processing, Modeling, Evaluation, and Dissemination. The data that is processed is 620 data consisting of class of students in 2014, 2015, 2016. The results of processing using clustering obtained 6 clusters that have different models for each cluster. The results of this study can be used by schools in recommending courses chosen by students according to students' interests and talents, so students can learn optimally.Key words: clustering, dataMining, suitability, majors, students
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