Efficiency of hybrid algorithm for COVID-19 online screening test based on its symptoms

Abstract

The coronavirus COVID-19 is affecting 196 countries and territories around the world. The number of deaths keep on increasing each day because of COVID-19. According to World Health Organization (WHO), infected COVID-19 is slightly increasing day by day and now reach to 570,000. WHO is prefer to conduct a screening COVID-19 test via online system. A suitable approach especially in string matching based on symptoms is required to produce fast and accurate result during retrieving process. Currently, four latest approaches in string matching have been implemented in string matching; characters-based algorithm, hashing algorithm, suffix automation algorithm and hybrid algorithm. Meanwhile, extensible markup language (XML), JavaScript object notation (JSON), asynchronous JavaScript XML (AJAX) and JQuery tehnology has been used widelfy for data transmission, data storage and data retrieval. This paper proposes a combination of algorithm among hybrid, JSON and JQuery in order to produce a fast and accurate results during COVID-19 screening process. A few experiments have been by comparison performance in term of execution time and memory usage using five different collections of datasets. Based on the experiments, the results show hybrid produce better performance compared to JSON and JQuery. Online screening COVID-19 is hopefully can reduce the number of effected and deaths because of COVID.