Chronic Kidney Disease Severity Identification Using Template Matching Feature Selection Statistics Based

The number of patients with Chronic Kidney Disease is currently increasing in this decade. This needs to be a concern, especially in determining the severity level from the start. Chronic Kidney Disease consists of 5 grades from Grade 1 to Grade 5, where Grade 1 indicates the mildest condition and Grade 5 is the most severe condition. Determining the severity of this is very important because on the basis of this level of severity can be determined the next step of healing. This study aims to propose a way to identify Chronic Kidney Disease severity using a template matching feature selection statistics based. This research stage is the stage of data initialization, statistical analysis, and the trial process using eucledian distance. The experiments carried out were divided into 4 parts, namely using 26 parameters (based on mean data) and using 28 parameters (based on mode data). The results show that the accuracy value obtained is 76.88%. The results of the analysis show that the age parameter is not a significant parameter to cause Chronic Kidney Disease, meaning that this disease can occur in all age groups.