Website based application of doctor selection classification derive from patient complaints using the c4.5 method and k-nearest neighbor

Abstract

This paper is about web based application of doctor selection classification, derive from patient complaints by utilizing the C4.5 method and K-Nearest Neighbor. Classification is the process of grouping things based on classes with the characteristics of similarities and differences. This objects or entities are labeled as user complaints. User complaints are classified and produce a category of doctor that matches the user's complaints. This application will be using sample data from ascertain the opinions and experience of Doctor Yohannes Cahyadi who practices at the Griya Kasih Indah Clinic and from the website alodokter, hellosehat, docdoc.com, cicendoeyehospital, and the eye clinic Nusantara. The purpose of making a doctor selection classification application based on patient complaints is so that the user can find out the doctor's category recommendations in accordance with user complaints input on this application. The test results obtained said that the best classification accuracy is to use the K-Nearest Neighbor method with an accuracy value of 100%, this shows that the use of the C4.5 method and K-Nearest Neighbor can provide recommendations for the right doctor with user complaints.