首页> 外文期刊>Jurnal Teknologi Informasi dan Komunikasi >PREDIKSI PENENTUAN BAKAT DAN MINAT SISWA DENGAN MENGGUNAKAN METODE CART (CLASSIFICATION AND REGRESSION TREE) (STUDI KASUS: Madrasah Aliyah Al Hadi Girikusuma)
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PREDIKSI PENENTUAN BAKAT DAN MINAT SISWA DENGAN MENGGUNAKAN METODE CART (CLASSIFICATION AND REGRESSION TREE) (STUDI KASUS: Madrasah Aliyah Al Hadi Girikusuma)

机译:使用购物车(分类和回归树)方法确定学生人才和兴趣的预测(案例研究:Madrasah Aliyah Al Hadi Girikusuma))

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The determination of talent and interest is the determination of majors that are introduced by Senior Hight School. Madrasah Aliyah Al Hadi Girikusuma is a private madrasah of Senior Hight School and vocational high school that also implements the process of determining talent and interest for their students. Participants in the determination of talents and interests followed by the participants of class X with the number of participants as many as 124 students. The number of students and the process that is still manual makes the old and less efficient in the determination of talents and interests. This quantitative research predicts the determination of student's talents and interests by using CART Classification And Regression Tree method and using Repied Miner 5.3.013 tools. which will define some labels, resulting in 3 status predictions, namely IPA, IPS and Religion. Processed data using 3 variable indicators include knowledge variables, practice variables and attitude variables from each subjects under the control. The result of CART classification with accuracy from experiment using Fold Cross validation method with sampling type using shuffled sampling yield accuracy of 73.40%, precision of 82.43% and recall of 80.26%.
机译:人才和兴趣的决心是高级高校介绍的专业的决心。 Madrasah Aliyah Al Hadi Girikusuma是一个私人高级学校和职业高中的私人Madrasah,也有助于确定学生人才和利益的过程。参与者在确定人才和兴趣之后,X类与参与者的参与者有多达124名学生。学生的数量和仍然是手动的过程使得旧的和较低的效率在确定人才和兴趣方面。这种定量研究通过使用购物车分类和回归树方法并使用Crefied Miner 5.3.013工具来预测学生人才和兴趣的确定。这将定义一些标签,导致3个状态预测,即IPA,IPS和宗教。使用3变量指示符的处理数据包括知识变量,从控制下的每个受试者的实践变量和姿态变量。随着使用折叠式抽样型折叠式验证方法,使用折叠式取样率,使用折叠式抽样效果精度为73.40%,精度为82.43%,召回80.26%的折叠式型号,召回的折叠交叉验证方法的结果。

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