Implementasi Sistem Pakar Pemilihan Obat Berdasarkan Gejala Penyakit Flu Singapura Menggunakan Metode Naïve Bayes
Keywords:
Expert System, HFMD, Naïve Bayes, RAD, Website, DiagnosisAbstract
Hand, Foot, and Mouth Disease (HFMD) is a contagious illness that commonly affects children and may cause discomfort, especially in densely populated areas. The difficulty in recognizing early symptoms and selecting the appropriate medication often hinders effective treatment. This study aims to design an expert system to assist the public in diagnosing HFMD symptoms and providing drug recommendations using the Naïve Bayes method. The system was developed as a website-based application to ensure ease of access for the people of Bogor City. The development followed the Rapid Application Development (RAD) methodology, with data obtained from medical sources and expert interviews. System testing was conducted by comparing system-generated diagnoses with expert opinions, resulting in a classification accuracy of 91.7%. These results indicate that the system can be a reliable early diagnostic tool and may assist the public before seeking medical consultation.
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