Covid-19 Risk Model Development Using Fuzzy Logic For The Reopening Of Face-To-Face Classes - Candia Jr, Jose; Gonzales, Ike; Frayco, Joenil; Jabel, Cristy Lou; Ronquillo, Ariston; Sambalod, Zarina Gail D. (Journal of Engineering and Science Application, 2025)
COVID-19 pandemic had caused a global crisis in the education sector due to the urgent closure of schools to prevent the spread of the virus. After so much effort to curb the transmission of Coronavirus, the Philippine government has finally approved the re-opening of face-to-face classes in colleges and universities. However, responding to educational needs might pose COVID risks to the academic community. Thus, this study used the Fuzzy Logic to develop a model to measure the risk associated with COVID under the Northeastern Mindanao State University – Tagbina campus condition. Results showed that developed model using Fuzzy Logic algorithm produced satisfying result after expert validation in assessing Covid-19 risk transmission. Further, using the developed model, the campus has 38.5% risk, classified as "Low”. Despite challenges in opinions of multiple experts, the model was able to draw conclusion in support to campus management’s decision-making pertaining to campus risk of covid transmission.