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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Fadil Idensia
Universitas Putra Indonesia “YPTK” Padang, Indonesia
Computer Science & IT Control & Systems Engineering

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Penerapan Teorema Bayes Pada Sistem Pakar Untuk Mendeteksi Dini Penyakit Tuberkulosis (Studi Kasus Di Rs. Tentara Dr. Reksodiwiryo Padang) Fadil Idensia; Y Yuhandri; Billy Hendrik
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 2 (2024): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i2.369

Abstract

Tuberculosis (TB) is an infectious disease that is still a global health problem, including in Indonesia. Early detection of this disease is crucial for effective treatment. In order to improve early detection of TB, this research aims to apply the Bayes Theorem method to the development of an expert system. The case study was conducted at Dr. Reksodiwiryo, Padang, where the percentage of Tuberculosis based on the method has been identified. The Bayes Theorem method is implemented in an expert system to provide early diagnosis to patients suspected of having TB. Expert system testing was carried out to evaluate the accuracy of the diagnosis, with an average calculation result using Bayes' theorem of 80%. The results of this research indicate that the application of Bayes' Theorem in an expert system can be an effective tool in early detection of Tuberculosis. The practical implication of this research is to increase the capabilities of the Dr. Army Hospital. Reksodiwiryo Padang in treating TB early and accurately, as well as contributing to efforts to prevent and control this disease more efficiently.
Co-Authors Billy Hendrik Y Yuhandri