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Habinata Habinata
Institut Teknologi dan Bisnis Bina Sarana Global
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Expert System Prediction of Covid-19 Transmission Vulnerability using Forward Chaining Habinata Habinata; Rachmat Agusli; Detin Sofia
JURNAL SISFOTEK GLOBAL Vol 13, No 1 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i1.3504

Abstract

Covid-19 is a pandemic that is currently sweeping the world, where the number of infected victims has reached millions. The sudden outbreak of the Covid-19 pandemic has caused unprepared communities to panic and worry, although there are also those who are indifferent or unconcerned about this contagious disease, which is a major factor in the rapid spread of the virus. This study aims to build a system to predict the vulnerability of users to contracting Covid-19 through an expert system application. The expert system method uses forward chaining to determine the user's vulnerability level based on factors used and inputted by the user. The large number of patients who still do not believe in the existence of Covid-19 and the spread of hoax news complicates the handling of Covid-19. With an expert system that predicts vulnerability to contracting the Covid-19 virus as a tool, it can increase awareness among low-awareness communities and reduce the spread of the Covid-19 virus.
Co-Authors Detin Sofia Rachmat Agusli