M. Alamsyah, Z. Nafisah, E. Prayitno, A.M. Afida, E.M. Imah
Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM. © Published under licence by IOP Publishing Ltd.
Mathematics Department, Universitas Negeri Surabaya, Ketintang, Surabaya, East Java, 60231, Indonesia
