Penerapan Metode Certainty Factor Dalam Mendiagnosa Penyakit Otitis Eksterna

Abstract

Otitis externa is a common ear problem that often requires an accurate diagnosis for effective treatment. The Certainty Factor Method is an artificial intelligence approach used to support the diagnostic process. This research aims to apply the Certainty Factor Method in diagnosing otitis externa. Patient data, including symptoms, medical history, and examination results, are used to build a knowledge base that is then utilized in the diagnostic process. This method allows for improved accuracy in determining diagnoses by considering the confidence level associated with each symptom and examination result. Experimental results show that the application of the Certainty Factor Method can assist doctors in diagnosing otitis externa with higher accuracy compared to conventional methods. With this approach, diagnoses are made with higher confidence levels, which can aid in providing accurate and prompt treatment for patients suffering from otitis externa. The Certainty Factor Method has the potential for use in other medical contexts and can make a positive contribution to problem-solving in the healthcare field. This research underscores the importance of technology in supporting ear disease diagnosis and providing more reliable solutions for managing otitis externa. By leveraging the Certainty Factor approach, doctors can be more efficient and effective in responding to patients' conditions, thus reducing the risk of complications and enhancing healthcare quality. Therefore, this study offers a valuable contribution to the fields of medicine and computer science in improving the diagnosis of ear diseases, such as otitis externa, so that patients can receive better and faster care.