Penerapan Algoritma Naïve Bayes dan Forward Selection Untuk Prediksi Penyakit Stroke

Abstract

Stroke is a major health problem in today's elite society. Currently, stroke is a serious problem that can occur in almost all parts of the world. A sudden stroke can cause death, physical and mental disability in both able-bodied and elderly people. In order to get batch data, one has to use data mining methods for classification, like Classification is the process of defining a concept or data class that describes or differentiates instances to evaluate an unknown class of objects. When classifying multiple attributes, a set of records is also defined, also known as an array. In continuous or categorical form, one of the attributes indicates the category of the record. With the dash problem above, of course, you have to be able to overcome this problem, a lot of research has been carried out in the field of computer science, including the Classification of Stroke Patients Using the Naïve Bayes Algorithm to classify the most important factors for this disease. Testing resulted in a fairly high accuracy of the Naïve Bayes Algorithm, which is equal to 95.13, but the results of this accuracy can still be improved by conducting further research to produce higher accuracy.