Sistem Pakar dalam Diagnosis Penyakit Cacar Monyet Menggunakan Metode Dempster Shafer Berbasis Web

Abstract

Monkeypox is a zoonotic disease caused by the monkeypox virus and can be transmitted from animals to humans as well as between humans. Its global spread since 2022, including in non-endemic regions such as Europe and America, highlights the importance of early detection and preventive efforts, especially in developing countries like Indonesia. Unfortunately, the limited number of experts and low public awareness have become obstacles to early diagnosis and effective response. This study aims to develop a web-based expert system that can assist in diagnosing monkeypox and distinguishing it from other types of smallpox. The system was developed using PHP as the programming language and MySQL as the database management system, and it applies the Dempster Shafer method as an inference technique to process symptoms based on belief levels. The system was tested through various case scenarios and produced accurate and relevant diagnostic results. In addition to its diagnostic function, the system also provides educational content related to monkeypox, including common symptoms and early treatment steps. With this system, the public is expected to gain access to reliable information and conduct initial self-diagnoses when needed. Furthermore, the expert system can serve as a useful tool for healthcare workers in accelerating the identification and response to monkeypox cases in the field.