SISTEM DETEKSI AWAL PENYAKIT TBC DENGAN METODE CBR

Abstract

TB disease is one of the contributors to the highest cause of death in Indonesia, this is because of late handling, late handling will be avoided if it can be done early detection of TB disease, this research tries to make alternatives that can be used for early detection TB disease. Case-Based Reasoning has been widely applied in various artificial intelligence, both in the form of expert systems and decision-making systems that help decision makers to make informed decisions. The use of CBR to diagnose illness has also been done by some previous researchers. Case-Based Reasoning works by studying previous cases collected in a General Knowledge that will be comparable with the new case, Case-Based Reasoning has four stages: Retrieve, Reuse, Revise and Retain, this is a very powerful way to create an expert system created into a learner engine, which automatically adds or revives knowledge automatically into the general knowledge. Expected by the implementation of Case-Based Reasoning in this system can help decision makers in this case early detection of TB disease, this sample was chosen because the number of sufferers of this disease is quite large in Indonesia.

Keywords: Case-Based Reasoning, Profile Matching, Expert System, TBC