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

  • Kristiyo Indriadi Wardoyo Universitas Dehasen Bengkulu
  • Maryaningsih Maryaningsih Universitas Dehasen Bengkulu
  • Jhoanne Fredricka Universitas Dehasen Bengkulu
DOI: https://doi.org/10.37676/jmi.v19i1.3307
Keywords: Keywords: Clustering, System of Persons with Disabilities, Level of Mental Retardation, K-Means Algorithm.

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

 

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Published
2023-04-07
How to Cite
Wardoyo, K., Maryaningsih, M., & Fredricka, J. (2023). KLASTERISASI SISWA PENYANDANG DISABILITAS BERDASARKAN TINGKAT TUNAGRAHITA MENGGUNAKAN ALGORITMA K-MEANS. JURNAL MEDIA INFOTAMA, 19(1), 1-10. https://doi.org/10.37676/jmi.v19i1.3307
Issue
Vol 19 No 1 (2023): April
Section
Articles

Copyright (c) 2023 Kristiyo Indriadi Wardoyo; Maryaningsih Maryaningsih, Jhoanne Fredricka

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