Sistem Pakar Deteksi Covid-19 Dengan Lie Detection Menggunakan Metode Circle Hough Transform

Bagus Priambodo; Yuwan Jumaryadi

doi:10.47065/josyc.v4i1.2528

Bagus Priambodo * Universitas Mercu Buana, Jakarta, Indonesia https://orcid.org/0000-0002-9459-0405
Yuwan Jumaryadi Universitas Mercu Buana, Jakarta, Indonesia

(*) Corresponding Author

DOI: https://doi.org/10.47065/josyc.v4i1.2528

Keywords: Healthcare Application; Covid 19; Circle Hough Transform; Lie Detection; Expert System

Abstract

The number of health workers infected with Covid-19 in Indonesia continues to grow amid the coronavirus pandemic. Not only doctors, nurses and other medical support staff have been exposed to Covid-19. To date, IDI has recorded more than 180 health workers who have died from Corona. Health workers are dying because of a lack of Personal Protective Equipment (PPE) and fatigue. Prevention of direct contact between asymptomatic patients and health workers is a way to prevent health workers from contracting COVID-19. An expert system for diagnosing COVID-19 with lie detection is proposed to be used for patients who wish to seek treatment at a health center before they meet face-to-face with health workers. Several previous studies have proven that the certainty method can be used to diagnose COVID-19 with an accuracy of up to 90%, provided that the patient answers questions honestly. In this study, control questions and pupil detection were added using the circle hard transform to find out whether patients who wanted treatment did not lie when answering questions about symptoms of exposure to Covid, travel history and family history of exposure to Covid. The combination of an expert system and lie detection is expected to be the first protective alternative for health workers from asymptomatic patients. Based on the results of the application testing carried out, it can be seen that the movement of the patient's pupils when answering questions.

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