Performance Comparison of the Kernels of Support Vector Machine Algorithm for Diabetes Mellitus Classification

Diabetes Mellitus is a disease where the body cannot use insulin properly, so this one of health problems in various countries. can be fatal, cause other diseases, and even lead to death. Based on this, it essential have prediction activities find out disease. The SVM algorithm used classifying diseases. This study aimed compare accuracy, precision, recall, F1-Score values with kernels data preprocessing. Data preprocessing included splitting, normalization, oversampling. research has benefit solving based percentage as material for accurate information. results are that highest accuracy was obtained by 80% (obtained from polynomial kernel), precision 65%, which also kernel, recall 79% RBF kernel) F1-score 70% (which kernel).