Classification in the Self Monitoring System for Chronic Kidney Failure Patients on Hemodialysis Therapy with SVM

Abstract

Patients with chronic kidney failure (CKF) need intensive care or therapy. Chronic kidney failure is a condition when kidney function decreases gradually due to damage to kidney tissue. Patients with these conditions need to undergo hemodialysis therapy which can be done every week. The results of this therapy need to be monitored to determine the quality and action after therapy. Monitoring of therapeutic results was initially carried out with medical records where the files were kept by the health agency. In addition, patients need to consult a doctor or nurse to read this medical record. This becomes an obstacle for patients to know the progress of their therapy results. Therefore it is necessary to have a monitoring system as a management information system for patients with chronic kidney failure. Conventional monitoring systems need to include visualization methods or quality fees from doctors. Therefore it is necessary to include the classification method as knowledge of the system to study patterns or rules from doctors in handling the quality of therapeutic results. This classification method uses the Support Vector Machine (SVM) with the Linear kernel as the classification method. In this study, the accuracy obtained with SVM was 90% with a short data training processing time.