Implementasi Sistem Pakar Menggunakan Metode Certainty Factor Untuk Mendiagnosa Dini Corona Virus Desease (COVID-19)

Abstract

Humans are facing a non-natural disaster that threatens the entire human population on Earth. Non-natural disaster is called Corona Virus Desease (COVID-19), which is a large family of viruses that can attack humans and animals that are currently a global pandemic. Humans usually cause respiratory infections, ranging from the common cold to serious illnesses such as MERS and SARS. COVID-19 itself is a new type of coronavirus found in humans and in the Wuhan area, Hubei Province, China in 2019. To assist medical staff in early detecting symptoms experienced by patients and facilitate the administration of hospital records, one of them was made an expert system that could detect this COVID-19 early with the Certainty Factor (CF) method. This expert system mimics similar symptoms experienced by COVID-19 patients and will be grouped into several patient statuses. Patients who experience serious symptoms will be grouped into Patients Under Supervision (PDP) and patients who are considered to have milder symptoms will be grouped into Insider Oversight status (ODP) while those who experience symptoms that are outside of the main symptoms will be classified into Non Suspect (NON) status . From 152 patient data inputted in this study, 114 ODP results with an average CF value of 91.38%, 36 PDP with an average CF value of 98.25% and 2 NONs with an average CF value of 40%. CF with system calculation experiments that represent patients get a CF value of 0.998848 or 99.88% to PDP. This expert system can be used to make decisions that can help medical personnel perform actions and administer better before conducting a through test in the laboratory to ensure positive or negative patients COVID-19