Abstract
Abstract: Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis that can affect the lungs and other organs of the body. The diagnosis of TB requires further medical examination; however, an initial diagnosis based on clinical symptoms can help provide preliminary information to the community. This study aims to design and develop an expert system that can assist in the initial diagnosis of tuberculosis based on clinical symptoms using the Certainty Factor method. This research was conducted at Teluk Nibung Public Health Center using a Mixed Methods approach, which involved qualitative data collection through interviews with relevant parties and quantitative data processing in the form of Measure of Belief (MB) and Measure of Disbelief (MD) values. The system was developed as a web-based application using PHP and MySQL and designed using UML modeling. The Certainty Factor method is used to calculate the degree of certainty of possible diseases based on the relationship between symptoms, MB values, MD values, and the user's level of confidence in the selected symptoms. The result of this research is an expert system application that can receive symptom and user confidence inputs, perform Certainty Factor calculations, display initial diagnosis results along with the percentage of confidence, and store diagnosis history. This system is expected to assist Teluk Nibung Public Health Center in providing initial tuberculosis diagnosis information to the community. The diagnosis provided by the system is not a substitute for a doctor's diagnosis or further medical examination. Keywords: Expert System, Tuberculosis, Certainty Factor, Initial Diagnosis, Clinical Symptoms. Abstrak: Tuberkulosis (TB) merupakan salah satu penyakit menular yang disebabkan oleh bakteri Mycobacterium tuberculosis dan dapat menyerang paru-paru maupun organ tubuh lainnya. Proses diagnosis TB memerlukan pemeriksaan medis lebih lanjut, namun diagnosis awal berdasarkan gejala klinis dapat membantu memberikan informasi awal kepada masyarakat. Penelitian ini bertujuan untuk merancang dan membangun sistem pakar yang dapat membantu melakukan diagnosis awal penyakit tuberkulosis berdasarkan gejala klinis menggunakan metode Certainty Factor. Penelitian ini dilakukan di Puskesmas Teluk Nibung dengan menggunakan pendekatan Mixed Methods, yaitu pengumpulan data secara kualitatif melalui wawancara dengan pihak terkait dan pengolahan data secara kuantitatif dalam bentuk nilai Measure of Belief (MB) dan Measure of Disbelief (MD). Sistem dikembangkan berbasis web menggunakan PHP dan MySQL serta dirancang menggunakan pemodelan UML. Metode Certainty Factor digunakan untuk menghitung tingkat keyakinan terhadap kemungkinan penyakit berdasarkan hubungan antara gejala, nilai MB, nilai MD, dan tingkat keyakinan pengguna terhadap gejala yang dipilih. Hasil penelitian berupa aplikasi sistem pakar yang dapat menerima input gejala dan tingkat keyakinan pengguna, melakukan perhitungan Certainty Factor, menampilkan hasil diagnosis awal beserta persentase tingkat keyakinan, serta menyimpan riwayat diagnosis. Sistem ini diharapkan dapat membantu Puskesmas Teluk Nibung dalam memberikan informasi diagnosis awal tuberkulosis kepada masyarakat. Hasil diagnosis dari sistem bukan merupakan pengganti diagnosis dokter atau pemeriksaan medis lebih lanjut.
