Pengelompokan Siswa Penyandang Disabilitas Berdasarkan Tingkat Tunagrahita Menggunakan Algoritma K-Medoids - Rousyati, Rousyati; Wati, Fanny Fatma; Pratmanto, Dany; Crisna, Aditia (Indonesian Journal on Software Engineering (IJSE), 2019)
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