KLASTERISASI SISWA PENYANDANG DISABILITAS BERDASARKAN TINGKAT TUNAGRAHITA MENGGUNAKAN ALGORITMA K-MEANS

Kristiyo Indriadi Wardoyo, Maryaningsih Maryaningsih, Jhoanne Fredricka
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Abstract

ABSTRACT:SLB Negeri 1 Bengkulu City is one of the special schools in Bengkulu City that provides educational facilities for children with special needs with mental retardation so that they can get a proper education in teaching and learning process. In the class placement of students in schools, mental retardation is divided into 2 levels, namely mild and moderate by observing by looking at the IQ scores of students and the academic scores obtained. This is necessary, so that the teaching and learning process becomes more efficient and effective. However, sometimes the school has difficulty in determining class placement for students with special needs for mental retardation, because there is no application that can help grouping the student data. Application for clustering students with mental retardation at SLB Negeri 1 Bengkulu City by applying K-Means algorithm. This application is made using Visual Basic.Net programming language and SQL Server database. Based on the student clustering that has been carried out based on a data sample of 73 students using the application, the results obtained information that 47.9% of the Cluster 1 group (mild mental retardation level) and 37% of the Cluster 2 group (moderate mental retardation level) and 15.1% of the Cluster 3 group (severe mental retardation level) from the calculation of the Euclidean distance value by taking the closest distance
残疾学生的统计标准是基于识字算法
摘要:本城第一小学是本城的一所特殊学校,为有特殊需要的智障儿童提供教育设施,使他们在教学和学习过程中得到适当的教育。在学校对学生的分班中,通过观察学生的智商分数和学业成绩,将智力低下分为轻度和中度两个等级。这是必要的,这样教学和学习过程变得更加高效和有效。然而,有时学校很难确定有特殊需要的智力迟钝学生的班级安排,因为没有可以帮助分组学生数据的应用程序。应用K-Means算法聚类Bengkulu市SLB Negeri 1智力迟钝学生。本应用程序是使用Visual Basic编写的。Net编程语言和SQL Server数据库。基于使用该应用程序的73名学生的数据样本进行学生聚类,结果得到的欧几里得距离值的计算结果为:47.9%的聚类1组(轻度智力迟钝)、37%的聚类2组(中度智力迟钝)和15.1%的聚类3组(重度智力迟钝)
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