Pengelompokan Siswa Penyandang Disabilitas Berdasarkan Tingkat Tunagrahita Menggunakan Algoritma K-Medoids

Rousyati Rousyati, Fanny Fatma Wati, Dany Pratmanto, Aditia Crisna

Abstract


Abstract: Mentally retarded children have obstacles in the activity of the name of the child who still needs proper education in the learning process. SLB Shanti Yoga is one of the best schools that provides educational facilities for children with special needs for people with mental disabilities. The number of criteria determining the level of mentally retarded students makes SLB Shanti Yoga have difficulty in dividing the class according to the results of observations made. So from that research was made to classify data on students with mental retardation to determine the class occupied so that the school can prepare it. The K-Medoids algorithm of clustering techniques can help in grouping students who will occupy classes including light, medium, and heavy classes. The class that has the highest number of students is the heavy mental retardation class while the class that has the lowest number of students is the moderate mental retardation class, with known data grouping results, SLB Shanti Yoga can prepare the class to be used for teaching and learning activities.

Keywords: Mentally retarded, data mining, clustering, K-Medoids

Full Text:

Untitled

References


Gorunescu, Florin. (2011). Data Mining Concept, Model and Technique. Verlag Berlin Heidelberg: Springer.

Han, J.,& Kamber, M. (2006). Data Mining Concept and Tehniques. San Fransisco: Morgan Kauffman. ISBN 13: 978-1-55860-901-3

Mediaindonesia.com

Pandji, Dewi dan Wardhani, Winda. (2013). Sudahkah Kita Ramah Anak Special Needs?. Jakarta: PT Elex Media Komputindo

Panti Asuhan Binasiwi. (2015). Menghapus Stigma Membangun Percaya Diri Anak Tunagrahita Melalui Pemberdayaan Partisipatoris. Yogyakarta: Lintang Pustaka Utama

.

Pieter, Herri Zan. (2017). Dasar-Dasar Komunikasi Bagi Perawat. Yogyakarta: PT. Kharisma Putra Utama

Suyanto. (2017). Data Mining Untuk Klasifikasi dan Klasterisasi Data. Bandung:Informatika.

Tan, Thomas. (2017). Teaching Is an Art: Maximize Your Teaching. Yogyakarta: Deepublish

Witten, H. I., Eibe, F., & Hall, A. M. (2011). Data Mining Machine Learning Tools and Techiques. Burlington: Morgan Kaufmann Publisher.

Zayuka, Harival, Nasution, S.M, Purwanto Yudha. (2017). Perancangan Dan Analisis Clustering Data Menggunakan Metode K-Medoids Untuk Berita Berbahasa Inggris

Design And Analysis Of Data Clustering Using K-Medoids Method

For English News. Bandung: E-Proceeding Of Engineer




Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Copyright Universitas Bina Sarana Informatika - ISSN : 2461-0690