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All Journal GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur)
Sahlino Sahlino
Department of Information Systems, Faculty of computer science, Universitas Dehasen Bengkulu
Civil Engineering, Building, Construction & Architecture Computer Science & IT Energy Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering

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Application of Certainty Factor Methods in the Development of Expert Systems in Diagnosing Asthma Sahlino Sahlino; Dewi Suranti; Rizka Tri Alinse
GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Vol 2, No 2 (2021)
Publisher : Perkumpulan Dosen Muda (PDM) Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37638/gatotkaca.v2i2.426

Abstract

Asthma occurs due to inflammation of the respiratory tract that causes sufferers to experience shortness of breath and wheezing. Asthma symptoms can appear due to the influence of infection, pollution, or allergies. Asthma is a type of disease that causes symptoms of narrowing and inflammation of the respiratory tract resulting in shortness of breath or difficulty breathing. Asthma can be caused by several things, namely dust, smoke, animal fur, cold air, physical activity, etc. Asthma is classified into 3 types, namely mild asthma, moderate asthma, and severe asthma. This expert system in diagnosing asthma is used to facilitate patient consultation, where the patient enters some of the symptoms he is experiencing and the system will diagnose these symptoms to determine whether asthma is classified as mild asthma, moderate asthma, or high grade asthma. In assisting the diagnosis, this expert system has applied Certainty Factor Method by proving a fact with a certainty value against that fact. The advantage of the CF method is that it can measure something that is certain or uncertain in decision making in disease diagnosis expert systems. Expert system in diagnosing asthma is made using Visual Basic.Net Programming Language with SQL database. With this expert system, it can help diagnose asthma suffered by patients based on the symptoms felt by the patient and provide solutions to deal with the disease suffered by a patient. Based on the tests that have been carried out, the functionality of the expert system application in diagnosing asthma is running as expected, and the application is able to display the results of the disease diagnosis from the symptoms selected by the patient. 
Co-Authors Dewi Suranti Rizka Tri Alinse