Abstract
The COVID-19 pandemic has had a significant impact on global health and economies. This study aims to identify highly effective prevention strategies for mitigating the spread of COVID-19 using the Fuzzy Analytic Hierarchy Process (FAHP) method. The FAHP is a fuzzy logic-based extension of the Analytic Hierarchy Process (AHP) technique, allowing for the consideration of both tangible and intangible criteria. The study focuses on seven key criteria: social/physical measures, health monitoring, avoidance of unnecessary contact, hygiene practices, immunity/fitness, healthy diet, and sharing personal items. By involving three decision-makers, including a nurse, a Medical Officer (MO), and a Medical Assistant (MA), the relative weights of these criteria are calculated using pair-wise comparisons and Buckley's approach. The findings reveal that hygiene emerges as the most critical factor in preventing the spread of COVID-19, followed by social/physical measures and health monitoring. The study provides valuable insights for policymakers and healthcare professionals in selecting and implementing effective preventive measures to control the spread of COVID-19.
Metadata
| Item Type: | Article |
|---|---|
| Creators: | Creators Email / ID Num. Mohd Idris, Mohd Fazril Izhar fazrilizhar@uitm.edu.my Abd Aziz, Khairu Azlan khairu493@uitm.edu.my Abd Aziz, Nilam Sri Farhana UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Fuzzy logic T Technology > T Technology (General) > Information technology. Information systems |
| Divisions: | Universiti Teknologi MARA, Perlis > Arau Campus |
| Journal or Publication Title: | Journal of Computing Research and Innovation (JCRINN) |
| UiTM Journal Collections: | UiTM Journals > Journal of Computing Research and Innovation (JCRINN) |
| ISSN: | 2600-8793 |
| Volume: | 8 |
| Number: | 2 |
| Page Range: | pp. 112-123 |
| Keywords: | COVID-19, prevention strategies, Fuzzy Analytic Hierarchy Process (FAHP), pair-wise comparisons, hygiene, social/physical measures, health monitoring |
| Date: | 2023 |
| URI: | https://ir.uitm.edu.my/id/eprint/86886 |
