Diagnostic decision support system of chronic kidney disease using support vector machine

Kidney disease or commonly known as kidney failure is a condition when the renal function is declining that could result in the inability of the kidneys to perform their duties. Kidney disease patients have the potential to get into the chronic phase. Chronic kidney disease is a decrease in kidney function gradually during the three months which resulted in the cessation of kidney function in total. The purpose of this development is a decision support system for a doctor in diagnosing of the kidney disease patients. The system displays the results of predicting whether patients with renal disease have entered a phase of chronic kidney disease or not. The methodology of this study consists of two main phases: classification modeling and system development. Classification modeling consists of data collection, data preparation, data grouping, classification, rules extraction. System development was based on the extracted rules before. This study resulted in a system that can detect a chronic condition of kidney disease based on several factors with an accuracy of 98.34%.