Penilaian Terpadu Beban Kerja Fisik Dan Mental Di UKM Kuliner Menggunakan Cardiovascular Load Dan NASA-TLX
Keywords:
Ergonomi Terintegrasi, Beban Kerja Fisik, Beban Kerja Mental, UKM Kuliner, Beban KardiovaskularAbstract
Culinary small and medium-sized enterprises (SMEs) are labor-intensive sectors in which workers are required to cope with a combination of physical and mental workload in their daily work activities. However, ergonomic studies in this sector remain limited and generally assess workload in a partial manner. This study aims to conduct an integrated assessment of physical and mental workload among workers in culinary SMEs using both physiological and subjective approaches. A quantitative observational design was employed and conducted among culinary SME workers. Physical workload was assessed using Cardiovascular Load (CVL) based on heart rate responses during work activities, while mental workload was evaluated using the NASA Task Load Index (NASA-TLX). The results indicate that workers in culinary SMEs experience moderate to high levels of physical workload, primarily due to manual activities and prolonged standing durations. In addition, NASA-TLX results reveal moderate to high levels of mental workload, with mental demand, temporal demand, and effort identified as the main contributing dimensions. These findings demonstrate that physical and mental demands occur simultaneously and interact within a single work system, potentially increasing the risk of work-related fatigue and reducing the sustainability of worker performance. This study highlights the importance of applying an integrated ergonomic approach in evaluating work systems in culinary SMEs. By combining physiological indicators and subjective perceptions, this study provides a more comprehensive understanding of workload characteristics and serves as a scientific basis for designing more ergonomic and sustainable work system improvements.
References
Alotaibi, A., Gambatese, J., & Nnaji, C. (2024). Developing a novel energy-based approach for measuring mental workload. Heliyon, 10(3). https://doi.org/10.1016/j.heliyon.2024.e24828
Babaei, E., Dingler, T., Tag, B., & Velloso, E. (2025). Should we use the NASA-TLX in HCI? A review of theoretical and methodological issues around Mental Workload Measurement. International Journal of Human Computer Studies, 201. https://doi.org/10.1016/j.ijhcs.2025.103515
Bartolomei, M., Gervasi, R., Acconito, C., Angioletti, L., Cannizzaro, D., Balconi, M., Mastrogiacomo, L., & Franceschini, F. (2026). Evaluating mental workload: A taxonomic approach to evaluation tools based on ISO 10075. Applied Ergonomics, 130. https://doi.org/10.1016/j.apergo.2025.104659
Berthon, L., Bernard, F., Fleury, S., Paquin, R., & Richir, S. (2025). Multi-dimensional measurement of mental workload in industrial context: an experiment in the field of helicopter maintenance. Applied Ergonomics, 129. https://doi.org/10.1016/j.apergo.2025.104599
Braarud, P. Ø. (2021). Investigating the validity of subjective workload rating (NASA TLX) and subjective situation awareness rating (SART) for cognitively complex human–machine work. International Journal of Industrial Ergonomics, 86. https://doi.org/10.1016/j.ergon.2021.103233
Büchli, A., & Troche, S. J. (2025). The sensitivity of psychophysiological measures to changes in mental workload. International Journal of Psychophysiology, 217. https://doi.org/10.1016/j.ijpsycho.2025.113262
Chai, J., & Li, Y. (2024). Examining mental workload based on multiple physiological signals: Review of the multi-attribute task battery (MATB) technique. In Medicine in Novel Technology and Devices (Vol. 24). Elsevier B.V. https://doi.org/10.1016/j.medntd.2024.100340
Chambi Quiroz, N., Mauricio, D., Inche Mitma, J., & Sanga, C. (2025). Systematic literature review of Ergonomic evaluation methods in the mining sector (2015-2024). In Journal of Safety Science and Resilience (Vol. 6, Number 4). KeAi Communications Co. https://doi.org/10.1016/j.jnlssr.2025.100215
Darabzadeh, S., larestani, A., Esmaeili, R., Jalali, M., Farhadi, S., & Ghasemian, H. (2025). Balancing the strain: The dual burden of musculoskeletal discomforts and mental workload in dentists. Acta Psychologica, 261. https://doi.org/10.1016/j.actpsy.2025.105923
Goodridge, C. M., Gonçalves, R. C., Arabian, A., Horrobin, A., Solernou, A., Lee, Y. T., Bruneau, A., Lee, Y. M., & Merat, N. (2026). The impact of N-back-induced mental workload and time budget on takeover performance. Accident Analysis and Prevention, 225. https://doi.org/10.1016/j.aap.2025.108327
Heymer, J., Räpple, D., Ott, M., Dengler, F., Jaki, C., Bent, D., & Hegar, A. (2025). Use of personal protective equipment and cognitive load during cardiopulmonary resuscitation – A randomized cross-over simulation-based study. Resuscitation Plus, 23. https://doi.org/10.1016/j.resplu.2025.100936
Huang, H. B., Sang, K., Zhou, M., Yi, L., Liu, J. Q., Yang, C. Z., Law, B. H. Y., Schmölzer, G. M., & Cheung, P. Y. (2025). The perceived workload of first-line healthcare professionals during neonatal resuscitation. Resuscitation Plus, 21. https://doi.org/10.1016/j.resplu.2025.100866
Jame Chenarboo, F., Hekmatshoar, R., & Fallahi, M. (2022a). The influence of physical and mental workload on the safe behavior of employees in the automobile industry. Heliyon, 8(10), e11034. https://doi.org/10.1016/j.heliyon.2022.e11034
Jame Chenarboo, F., Hekmatshoar, R., & Fallahi, M. (2022b). The influence of physical and mental workload on the safe behavior of employees in the automobile industry. Heliyon, 8(10). https://doi.org/10.1016/j.heliyon.2022.e11034
Jin, M., Qian, R., Wang, J., Long, J., Yuan, Z., Zeng, L., Liao, D., Liu, X., Tang, S., & Huang, S. (2024). Influencing factors associated with mental workload among nurses: A latent profile analysis. International Journal of Nursing Sciences, 11(3), 330–337. https://doi.org/10.1016/j.ijnss.2024.04.002
Ma, J., Li, H., Fang, B., Zhao, Z., Mehmood, I., Arsalan, A., & Wang, L. (2025). Assessing physical and mental fatigue in construction workers: validating sweat lactate as a biomarker. Ain Shams Engineering Journal, 16(8). https://doi.org/10.1016/j.asej.2025.103484
Maretto, L., Battini, D., Faccio, M., Granata, I., & Jaber, M. Y. (2024). How does the application of augmented reality affect the mental workload of human workers? A collection of preliminary results. IFAC-PapersOnLine, 58(19), 760–765. https://doi.org/10.1016/j.ifacol.2024.09.210
Nino, V., Claudio, D., & Monfort, S. M. (2023). Evaluating the effect of perceived mental workload on work body postures. International Journal of Industrial Ergonomics, 93. https://doi.org/10.1016/j.ergon.2022.103399
Sellmann, T., Zöllner, K., Nur, M., Oendorf, A., Willmes-Pflüger, M., Wetzchewald, D., & Marsch, S. (2026). The NASA Task Load Index in simulated cardiopulmonary resuscitation. American Journal of Emergency Medicine, 100, 73–78. https://doi.org/10.1016/j.ajem.2025.11.007
Shafiei, S. B., Shadpour, S., & Shafqat, A. (2024). Mental workload evaluation using weighted phase lag index and coherence features extracted from EEG data. Brain Research Bulletin, 214. https://doi.org/10.1016/j.brainresbull.2024.110992
