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All Journal Jurnal Jaringan Telekomunikasi
Supriatna Dwi Atmaja Suprayitno
State Polytechnic of Malang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Journal : Jurnal Jaringan Telekomunikasi

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COVID-19 Disease Diagnosis Expert System with Certainty Factor Method using iOS-Based App Supriatna Dwi Atmaja Suprayitno; M. Nanak Zakaria; Ahmad Wilda Yulianto
Jurnal Jaringan Telekomunikasi Vol 12 No 3 (2022): Vol. 12 No. 03 (2022) : September 2022
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jartel.v12i3.336

Abstract

The drop in COVID-19 patients in Indonesia from January to February 2022 made many companies prepare policies to no longer enforce work from home. At the office, we can interact and meet other people directly and it is possible to be exposed to Covid-19 that could potentially become a new wave of COVID-19. This effect poses a serious risk to all people who come into contact with COVID-19-infected individuals or are close to them. The major course of action that may be performed when someone has COVID-19 is self-isolation and tracking anyone who is around or has a health condition associated to COVID-19. We require an iOS-based COVID-19 diagnosis expert system application to track the health status of everyone around us because we are unable to know the health status of everyone. The application uses artificial intelligence technology in the form of an expert system to check health conditions. The expert system replaces the role of the expert with the certainty factor method. This app should be used every time before entering a potentially crowded place to clarify tracking by using maps feature. In addition to COVID-19, this expert system can also diagnose diseases that have the same symptoms as Typhoid Fever and Pneumonia. The results of the expert system are in the form of diagnosing the user's health condition based on the symptoms given with a confidence level of up to 0.9999952130944 or 99.99952130944% for COVID-19, 0.9676 or 96.76% for Typhoid Fever, and 97% for Pneumonia.
Co-Authors Ahmad Wilda Yulianto M. Nanak Zakaria