Farihah et al. IJDM (2024) 7:1, pp 45-60 DOI: https://doi.org/10.24815/ijdm.v7i1.36714 Copyright: © 2024 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). RESEARCH ARTICLE Workload Analysis of Rapid Response Team Regional Disaster Management Agency at The Support Command Post of the COVID-19 Task Force Special Region of Yogyakarta Indonesia Tutik Farihah 1 , Didik Krisdiyanto 2 *, Murtono Murtono 3* , Khamidinal Khamidinal 2* 1 Department of Industrial Engineering, Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta 55281 Indonesia. 2 Department of Chemistry, Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta 55281 Indonesia. 3 Department of Physic Education, Faculty of Education, UIN Sunan Kalijaga Yogyakarta 55281 Indonesia *Corresponding author: didik_kris@yahoo.com Received 09 January 2024; Accepted in Revised Form 23 June 2024; Accepted 04 July 2024 Introduction The COVID-19 pandemic, the event that occurred for more than a year has caused many people to be infected, suffering leading to deaths. The rapid development of the virus, marked by the emergence of new variants such as the delta variant (B 1525, B117, E484 K), is considered more contagious, prompting many parties to remain vigilant, indicating that mutations are still occurring. With each new variant, the virus's infectiousness escalates, evident in the rising tally of COVID-19 cases. By June 2021, Indonesia had recorded 1,885,948 COVID-19 cases, with 53,373 fatalities, representing a mortality rate of 2.83%. This trend mirrors the situation in the Special Region of Yogyakarta, where the death rate among COVID-19 patients around 2.449%, based on 38,703 positive cases and 948 deaths as of April 27, 2021 (www. bnpb.com). The spread of the virus will lead to an increase in infected patients, potentially overwhelming healthcare facilities which make health teams and the government working Abstract This Study evaluated mental workload of Rapid Response Team ((RRT) Regional Disaster Management Agency in Special Region of Yogyakarta as funeral team along COVID-19 pandemic. Mental workload is formed due to differences between individual abilities and performance demands of a task within a certain time. NASA TLX is the most widely used mental workload measurement, capable of being used in several levels of workload and sensitive to low workloads. The Rapid Response Team is a team to ensure that the disaster management process carried out quickly, accurately, skilled personnel to back up the medical team who continue to work hard so that the handling of the pandemic virus is better, and the virus does not spread. In this study, the subject of research is the funeral team of Rapid Response Team ((RRT) Regional Disaster Management Agency in Special Region of Yogyakarta Indonesia. Sampling data was collected online and offline using the Goggle Form in the range March-April 2021. There are 28 team members of the RRT who filled out the questionnaire. Workload assessment using the NASA-TLX and OWL methods falls within the range of medium (45.58458; 0.610535), high (74.73789; 0.739889), and very high (87.7969; 0.879976), with an average workload value of high (75.9935; 0.748672). Based on statistical tests using paired t-tests and one-way ANOVA, both methods are declared to be equivalent. The dimension that predominantly contributes to workload according to the NASA TLX method is Effort, followed by Mental Demands. Meanwhile, the factor that predominantly forms the workload according to the OWL method is S2 (Environmental Workloads, sub-factors: improper temperature, chemical exposure), followed by S3 (Body Motion and Postural Workloads, sub-factors: stooping, standing). The research findings offer manual guidance for workload identification, particularly utilizing OWL, serving as the foundation for workload assessment for teams involved in COVID-19, particularly in Indonesia. Additionally, this study also demonstrates that the OWL method possesses the same level of reliability as the NASA-TLX method. Keywords: Workload, Pandemic COVID-19, RRT, NASA TLX, Overall Workload Level (OWL).