학술논문

An Interactive Dashboard to Support Policymaking of Reopening School on Covid-19 Pandemic
Document Type
Conference
Source
2022 IEEE 9th International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2022 IEEE International Conference on. :1-6 Jun, 2022
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Transportation
COVID-19
Pandemics
Computational modeling
Government
Education
Urban areas
Process control
clustering
covid-19
dashboard
decision making
predictive model
school reopen
Language
ISSN
2377-9322
Abstract
In mid-April 2020, UNESCO monitored 191 countries and stated that around 1.723 trillion students in the world were affected by the policy of school from home. It is feared that school closures could hamper the provision of education services and could disrupt the education process which will affect the level of quality of education. There is still no creation of a computational model for the spread of covid as the main framework for schools reopening safely during the pandemic situation. Although there is already a framework from WHO and the government, there is no measuring tool that can evaluate the effect of reopening schools while the Covid-19 pandemic. For this reason, this research seeks to produce a model for the spread of Covid-19 as a basis for determining policies for safely reopening schools during the pandemic. In this research, we produced a recommendation to reopen face-to-face learning in the form of a dashboard. Recommendations are given by predicting the number of cases in each subdistrict using a predictive model. The prediction results are also combined with the factors that have been determined by the government to give recommendations. The allotment of recommendations process involves a critical factor analysis process where we identify which factors are dominant as a basis of a controllable pandemic.