PERBANDINGAN K-MEANS DAN K-MEDOIDS UNTUK KLASTERING TINGKAT STRES PADA MANUSIA

Abstract

Society is faced with various problems as a result of progress and development of the times. Things in social relationships and demands from an expectation in achievement but not being met, from these inability and demands can cause stress in a person. Stress is the body's response caused by demands from outside the individual that exceed the ability to meet the demands to overcome and resolve the problem. The need to respond and manage stress well so that the quality of life becomes better, with clustering it can make it easier to group data. The clustering technique used is the K-Means and K-Medoids methods which partition the data into clusters. Comparison of cluster results used the use of a covariance matrix. So that in the comparison of the K-Means method k=2 and k=3, the best one is k=3 because the determinant of the covariance matrix is ​​smaller, namely -1.4709e-11. In the comparison of the K-Medoids method k=2 and k=3, the best one is k=3 because the determinant of the covariance matrix is ​​smaller, namely -1.4285e-11. Continued comparison of the two methods, namely K-Means and K-Medoids, the best is K-Medoids with a smaller covariance determinant than K-Means.