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Antoni
Universitas Islam Sumatera Utara
Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice

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Journal : Bulletin of Computer Science Research

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Aplikasi Diagnosa Epliepsi dengan Metode Certainty Factor pada Rumah Sakit Umum Daerah Kota Pinang Febrianti Mandasari; Antoni; Tasliyah Haramaini
Bulletin of Computer Science Research Vol. 2 No. 3 (2022): Agustus 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v2i3.171

Abstract

In the development of computer technology, computer technology has become an inherent part of human life when it comes to solving a more complex problem in various areas, including education, health, etc. One of the applications of information technology in the health field is an expert system for the identification of epilepsy. An expert system is a computer system that wants to replicate the decision making ability of an expert in all aspects. Epilepsy is the second most common neurological disorder in humans following stroke. The shortage of epilepsy specialists and the lack of tools to deal with epilepsy requires a system that can help the problem in the form of an expert system using certainty factor method to ensure that there are no misdiagnosis and to assist doctors in diagnosing epilepsy in patients quickly. As a research type, explanatory research is used using primary and secondary data types, the data collection method used is the method of interviewing and literature studies and the method of certainty factor with front chain reasoning techniques. This application requires data on disease symptoms, certainty factors of expert value and certainty factors of patients to get a confidence level for epilepsy diagnosis. Based on the results of the study, it can be concluded that the system is capable of providing confidence values, can diagnose epilepsy based on the symptoms entered by the user, and can provide a solution for epilepsy.
Co-Authors Andina Mei Vani Lubis Eddi Suprayitno Edi Azwar Faisal Hasiholan Purba Febrianti Mandasari Ferry Fachrizal - Julham Julham Mbera Mehuli Mochamad Dandi Akbar Mutia Chairunisa Nuraida Batubara Satria Yudha Prayogi Solly Arya Solly Aryza Sri Hastuti Br Saragih Tasliyah Haramaini Teddy Hardiansyah Yusrita . Zulkarnain Lubis Zulkarnain Lubis