TY  - JOUR
AU  - Wijaya, Dedy Rahman 
AU  - Agung, Anak Agung Gde 
AU  - Fahrudin, Tora 
AU  - Suryatiningsih, 
PY  - 2021
TI  - First-Degree Polynomial Gradient Approach to Reveal the Severity of COVID-19 Pandemic in Affected Countries
JF  - Journal of Computer Science
VL  - 17
IS  - 2
DO  - 10.3844/jcssp.2021.167.177
UR  - https://thescipub.com/abstract/jcssp.2021.167.177
AB  - COVID-19 is a new type of Coronavirus (2019-nCoV) which originated from Wuhan in China. Since 11 March 2020, WHO has declared COVID-19 as a pandemic. Currently, it has spread to 175 countries or regions around the world. From day to day, confirmed, recovered and death cases have been reported. This data rapidly changes that indicates an uncertain situation. This uncertain situation might affect many social-economic activities. However, until now, there is no approach to categorize these countries in conjunction with the latest situation. The typical measure, for example, the Case Fatality Rate (CFR) is used to measure the proportion of deaths compared to the total number of confirmed from a certain disease. It utilizes for diseases with discrete, limited-time courses, such as outbreaks of acute infections. The major drawback of CFR is it can only be considered as a final result when all the cases have been accomplished (either died or recovered). According to this gap, we proposed the first-degree polynomial or linear gradient approach to categorize the COVID-19 severity status of areas or countries based on the rate of confirmed, recovered and death cases. The status categorization is necessary information for all parties to be aware of the situation. It can be used for consideration to determine policies related to COVID-19 pandemic such as travel warning, self-isolation, work from home, lock-down, etc.