KLASTERISASI DATA DISABILITAS MENGGUNAKAN ALGORITMA K-MEANS

Abstract

Persons with disabilities are people who have physical or mental limitations that can affect them and interfere with normal daily activities. People with special needs (disabled) live with special characteristics and are different from the general public. So far, the placement of classes for students with disabilities is based on the child's entry age when registering at SLB N Tegal City, no Intelligence Quotient (IQ) test has been tried in grouping. This study aims to determine the results of class clustering of students with disabilities. In this study using data mining techniques with the K-Means clustering method. The K-Means method is a clustering method that is useful for breaking datasets into several groups. The source of this research data was obtained from SLB N Tegal City. The data entered is a sample of disability class data for 2021-2022 which is divided into 3 clusters, namely light, medium and severe clusters with an Intelligence Quotient (IQ) assessment. From the results of the k-means calculation, 11 students were found as a light cluster, 9 students as a medium cluster and 10 students as a heavy cluster. The clustering process uses excel and the RapidMiner application is used to help find accurate values.