PENERAPAN BAYESIAN PROBABILITY PADA SISTEM PAKAR PENDIAGNOSIS PENYAKIT

Abstract

Technological advances in the field of life do not only bring change to science and technology, but also provide significant changes in many areas of human life. One of the most important areas for humans is health. Health is very much related to disease. If a person's health is not well maintained, it will cause the person to become ill. Illness is something that is not normal. People who experience pain will usually consult with a doctor in order to be able to recover from his illness. Often a patient needs to find a doctor who is an expert in certain diseases in order to heal. But the problems that occur, sometimes difficult to find a doctor who is really an expert in certain diseases. To overcome these problems and with the development of computer technology, can be developed a system that can think and act like a doctor. The ability of a system that can think and act is called Artificial Intelligence (AI). AI is designed to work like humans who can think and act rationally with some reasoning and approaches. One of the special parts of AI is the Expert System programmed to implement some logical reasoning like humans. Expert systems are computer programs that mimic the reasoning of an expert with expertise in a particular area of knowledge. In designing an expert system required a method to be used as a reference in deciding the problems encountered. Methods in expert systems are numerous, one of which is Bayesian Probability (Bayes probability). Bayes probability is a way to overcome data uncertainty by using Bayes formula. Bayes probability is more applicable to statistical diagnosis-related matters relating to the probability and likelihood of disease and related symptoms. An expert system that thinks and acts by mimicking an expert's reasoning will result in a conclusion or solution. The reasoning of such thinking is carried out with several approaches to the problem and resembles a logical human mindset. Keywords: System, Expert, Disease, Probability, Bayes