Model Prediksi Penempatan Magang Siswa SMK menggunakan Teknik Association Rule Mining

Dwi Welly Sukma Nirad, Afriyanti Dwi Kartika, Aghill Tresna Avianto, Aulia Anshari Fathurrahman
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Abstract

Insternship activity is one of the core activities of every Vocational School (SMK) as the purpose of this school is to conduct education at the level of work-oriented readiness. Every SMK graduate is expected to be better prepared to enter the industrial world. However, in fact there were gaps that resulted in the unpreparedness of students after graduating from school. This research identified and analyzed the placement of student internships. The aim was to find an insternship placement pattern in order to get an overview and recommendation of an appropriate internship according to students abilities. The technique used was the association rule mining, a technique of the data mining method that was useful for uncovering the rules that were correlated to each other so that they can better organize and predict the internship placements. The results showed that the association rule mining could be applied to analyze student performance and predict internship placements in the future. This prediction could be a consideration for the teacher to determine the subjects that need to be improved to prepare students for internships.
实习活动是每所职业学校(SMK)的核心活动之一,因为学校的目的是在面向工作的准备水平上进行教育。每位SMK毕业生都有望为进入工业世界做好更好的准备。然而,实际上存在差距,导致学生毕业后没有做好准备。本研究确定并分析了学生实习的安置情况。目的是找到一个实习安排模式,以便根据学生的能力得到一个概述和合适的实习建议。所使用的技术是关联规则挖掘,这是数据挖掘方法中的一种技术,可用于发现相互关联的规则,以便更好地组织和预测实习位置。结果表明,关联规则挖掘可以用于分析学生的表现和预测未来的实习安排。这种预测可以作为教师确定需要改进的科目的考虑因素,以使学生为实习做好准备。
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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