Decision Support System Assessment Of Truck Driver Work Mental Load in Giwangan Market Area, Yogyakarta Using NASA-TLX

Riani Nurdin, Bagus Wahyu Utomo, Harliyus Agustian


Traditional markets in Indonesia have experienced a decline in performance as from 2002 to 2013. Sales value in 2002 was 74.8%, in 2005 the sales value of traditional markets was 67.6%, then in 2011 it was 55.8%. Giwangan Market is the largest traditional market in the area of Yogyakarta Province. However, many of the traditional markets have inadequate infrastructure both in terms of cleanliness and tidiness of the market location which is detrimental to truck drivers in these markets. Research shows that driver fatigue is the cause of road accidents by 30%. Regarding the measurement of mental workload, subjective measures of workload are easy to provide and have high assessment ability because the measurement is independent of the task. The Decision Support System Model can provide input to Giwangan Market managers to show the mental workload scale of truck drivers using the NASA-TLX Scale (Task Load Index) approach, the most widely used subjective scale by asking participants to rank separately on the mental command subscales. demand, physical demand, temporal demand, own performance, effort, and frustration level. The results of the system show that the mental workload of truck drivers in Giwangan Yogyakarta Market has a very high workload, as many as 4 drivers, 5 drivers have a high workload and 1 driver has a fairly high workload interpretation.


Truck Driver; Mental Workload; Decision Support System


Bener, A., Yildirim, E., Özkan, T., & Lajunen, T. (2017). Driver sleepiness, fatigue, careless behavior and risk of motor vehicle crash and injury: Population based case and control study. Journal of Traffic and Transportation engineering (English edition), 4(5), 496-502.

Bowden, Z. E., & Ragsdale, C. T. (2018). The truck driver scheduling problem with fatigue monitoring. Decision Support Systems, 110, 20-31.

Bowman, D. S., Schaudt, W. A., & Hanowski, R. J. (2012). Advances in drowsy driver assistance systems through data fusion. Handbook of intelligent vehicles, 2, 895-909.

Casali, J. G., & Wierwille, W. W. (1983). A comparison of rating scale, secondary-task, physiological, and primary-task workload estimation techniques in a simulated flight task emphasizing communications load. Human factors, 25(6), 623-641.

Chen, C., & Xie, Y. (2014). The impacts of multiple rest-break periods on commercial truck driver's crash risk. Journal of safety research, 48, 87-93.

Fraser, T. M. (1992). Stres & Kepuasan Kerja, Jakarta: PT. Pustaka Binaman Pressindo.

Global Agriculture Information Network., 2013, USDA Foreign Agriculture Service, GAIN Report Number: ID1358.

Hancock, P. A., & Meshkati, N. (Eds.). (1988). Human mental workload (pp. 139-183). Amsterdam: North-Holland.

Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In Advances in psychology (Vol. 52, pp. 139-183). North-Holland.

Huang, H., Peng, Y., Wang, J., Luo, Q., & Li, X. (2018). Interactive risk analysis on crash injury severity at a mountainous freeway with tunnel groups in China. Accident Analysis & Prevention, 111, 56-62.

Li, J., Du, J., & Li, L. (2018, October). Optimization of vehicle routing problem with fatigue driving based on genetic algorithm. In Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems (pp. 37-42).

Min, H., & Melachrinoudis, E. (2016). A model-based decision support system for solving vehicle routing and driver scheduling problems under hours of service regulations. International Journal of Logistics Research and Applications, 19(4), 256-277.

National Academies of Sciences, Engineering, and Medicine. (2016). Commercial motor vehicle driver fatigue, long-term health, and highway safety: research needs. National Academies Press.

Prabowo, F. S., & Rahadi, R. A. (2015). David vs. Goliath: Uncovering The Future of Traditional Markets in Indonesia. Mediterranean Journal of Social Sciences, 6(5), 28-28.

Priyono, M. M. (2013). Analysis of Traditional Market Development Strategy in The District Sidoarjo. IOSR Journal of Business and Management.

Stern, H. S., Blower, D., Cohen, M. L., Czeisler, C. A., Dinges, D. F., Greenhouse, J. B., ... & Wegman, D. H. (2019). Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health. Accident Analysis & Prevention, 126, 37-42.

Susilowati, K. D. S. (2014). The Impacts of modern market to traditional traders (a case in Malang City-Indonesia). International Journal of Technical Research and Applications, 2, 38-44.

Tsang, P. S., & Velazquez, V. L. (1996). Diagnosticity and multidimensional subjective workload ratings. Ergonomics, 39(3), 358-381.

Zheng, Y., Ma, Y., Guo, L., Cheng, J., & Zhang, Y. (2019). Crash involvement and risky riding behaviors among delivery riders in China: the role of working conditions. Transportation research record, 2673(4), 1011-1022.



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