Analisis Breadth-First Search dan Algoritma Certainty Factor untuk Diagnosa Penyakit Pada Mahasiswa

Abstract

The problem that often occurs, especially among students, is a lack of knowledge about disease symptoms, which can lead to difficulties in making an initial diagnosis and require assistance from medical experts. Students often have busy schedules and do not have enough time to undergo regular health check-ups, resulting in symptoms of diseases being overlooked and not detected quickly. Some students may not have access to adequate healthcare services, especially those living in remote areas or outside the city. Students often do not realize the importance of maintaining their health and undergoing regular health check-ups, which can worsen their health conditions. Therefore, a system is needed to assist students in quickly and accurately diagnosing diseases. This research aims to develop a disease diagnosis system for students using the breadth-first search method and certainty factor algorithm. This method utilizes calculations based on similarity divided by predetermined weights. Certainty factor (CF) is a clinical parameter value provided by experts to indicate the degree of confidence in a fact or rule. In this study, disease symptoms are inputted into an expert system and calculated using the certainty factor method to diagnose the type of disease suffered by students. The research results show that the developed expert system successfully diagnoses the type of disease with an accuracy of 97.5%.