Case-Based Reasoning untuk Diagnosis Penyakit Campak Menggunakan Metode Bayesian Model

Abstract

In the medical world, measles is an infectious disease that has long been known and is still a global health problem. Measles is divided into two main types, rubeola measles and rubella measles.This study is conducted to build a diagnose system for measles disease with CaseBased Reasoning (CBR). Case-based reasoning (CBR) is a method in artificial intelligence that solves problems by analyzing solutions from similar cases that have occurred before. CBR can eliminate the need to extract models or sets of rules. Knowledge acquisition in CBR is based on a collection of experiences or previous cases. The Bayesian model is used as indexing to find the type of measles CBR in this study. The test was carried out by using 35 cases that were stored in case base and 20 case bases serve as a new case.