Diagnosa Penyakit Syndrome pada Anak menggunakan Metode Case Base Reasoning (CBR)

Abstract

Syndrome is a serious problem in children's health because it has a major impact on growth and development, especially in terms of intelligence and daily activities. Down Syndrome, as one of the most well-known chromosomal disorders, is often the main cause of intellectual developmental disorders, hypotonia, facial dysmorphism, early onset of Alzheimer's disease, and various behavioral disorders. Diagnosing syndrome diseases in children is often difficult due to complex and varied symptoms, requiring lengthy, costly, and time-consuming medical evaluations. This study aims to design a Case-Based Reasoning (CBR)-based expert system for diagnosing syndromes in children, which is expected to help accelerate the disease identification process and provide more effective and efficient solutions. The method used is the development of an expert system with a CBR approach, in which the system performs calculations and matching based on the symptoms selected by the user against the available case base. The results of the study show that from symptom inputs such as wide hands with short fingers, short stature, small head, stunted growth, small lower jaw, abnormal body appearance, and weak joints, the system was able to diagnose Klinefelter syndrome with a percentage of 43.58%. This system can be an alternative for patients or families who have limited time and funds to obtain medical consultations, so that diagnosis and follow-up can be carried out more quickly and efficiently.