Work Performance Measurement of Data Entry Employees in E-Commerce Industry Based on Mental Workload Value
DOI:
https://doi.org/10.21512/comtech.v10i2.5688Keywords:
work performance, e-commerce, mental workload valueAbstract
This reseach aimed to measure the mental workload of data entry processing tasks in the e-commerce industry based on mental workload value. It was to determine the factors influencing mental workload mainly induced by the data entry process. The experiments without work instruction and with two types of work instruction were conducted to diagnose the mental workload. The measurement of the initial mental workload condition of data entry employees was conducted in the laboratory. Then, the Electroencephalogram (EEG) measurement using sensors from Emotiv was performed every 30 minutes, and the data of EEG measurements (focus, engagement, and stress) were collected using the laptop. Meanwhile, pulse measurement (heart rate) was measured before and after the work. Raw National Aeronautics and Space Administration Task Load Index (NASA-TLX) and reaction time measurement were conducted after the work. Through these experiments, the researchers identify that mental effort and fatigue are the significant determinants of mental workload value in the data entry process of the e-commerce industry. In respect of the results of work performance analysis, it is recommended that the placement of work instruction should be near the employee. Then, the task demand (minimum completion target) should be adjusted according to each employee’s capacity.
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References
Aribawa, D. (2016). E-commerce Strategic Business Environment Analysis in Indonesia. International Journal of Economics and Financial Issues, 6(6S), 130-134.
Barchard, K. A., & Verenikina, Y. (2013). Improving data accuracy: Selecting the best data checking technique. Computers in Human Behavior, 29(5), 1917-1922. https://doi.org/10.1016/j.chb.2013.02.021
Berka, C., Levendowski, D. J., Lumicao, M. N., Yau, A., Davis, G., Zivkovic, V. T., ... & Craven, P. L. (2007). EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. Aviation, Space, and Environmental Medicine, 78(5), B231-B244.
Borghouts, J., Soboczenski, F., Cairns, P., & Brumby, D. P. (2015). Visualizing magnitude: Graphical number representations help users detect large number entry errors. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (pp. 591-595). https://doi.org/10.1177/1541931215591130
Borghouts, J., Brumby, D., & Cox, A. (2017). Batching, error checking and data collecting: understanding data entry in a financial office. In Proceedings of 15th European Conference on Computer-Supported Cooperative Work-Exploratory Papers. https://doi.org/10.18420/ecscw2017-4
Bosch, T., Könemann, R., De Cock, H., & Van Rhijn, G. (2017). The effects of projected versus display instructions on productivity, quality and workload in a simulated assembly task. In Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments (pp.412-415). https://doi.org/10.1145/3056540.3076189
Brouwer, A. M., Hogervorst, M. A., Holewijn, M., & Van Erp, J. B. F. (2014). Evidence for effects of task difficulty but not learning on neurophysiological variables associated with effort. International Journal of Psychophysiology, 93(2), 242-252. https://doi.org/10.1016/j.ijpsycho.2014.05.004
Cain, B. (2007). A review of the mental workload literature. Retrieved from https://apps.dtic.mil/dtic/tr/fulltext/u2/a474193.pdf
Causse, M., Fabre, E., Giraudet, L., Gonzalez, M., & Peysakhovich, V. (2015). EEG/ERP as a measure of mental workload in a simple piloting task. Procedia Manufacturing, 3, 5230-5236. https://doi.org/10.1016/j.promfg.2015.07.594
Cheng, S., Lee, H., Shu, C., & Hsu, H. (2007). Electroencephalographic study of mental fatigue in visual display terminal tasks. Journal of Medical and Biological Engineering, 27(3), 124-131.
Galy, E., Cariou, M., & Mélan, C. (2012). What is the relationship between mental workload factors and cognitive load types? International Journal of Psychophysiology, 83(3), 269-275. https://doi.org/10.1016/j.ijpsycho.2011.09.023
Hogervorst, M. A., Brouwer, A. M., & Van Erp, J. B. F. (2014). Combining and comparing EEG, peripheral physiology and eye-related measures for the assessment of mental workload. Frontiers in Neuroscience, 8(October), 1-14. https://doi.org/10.3389/fnins.2014.00322
Hollnagel, E. (1997). Cognitive ergonomics: It’s all in the mind. Ergonomics, 40(10), 1170-1182. https://doi.org/10.1080/001401397187685
Julisar, J., & Miranda, E. (2013). Pemakaian e-commerce untuk usaha kecil dan menengah guna meningkatkan daya saing. ComTech: Computer, Mathematics and Engineering Applications, 4(2), 638-645. https://doi.org/10.21512/comtech.v4i2.2486
Käthner, I., Wriessnegger, S. C., Müller-Putz, G. R., Kübler, A., & Halder, S. (2014). Effects of mental workload and fatigue on the P300, alpha and theta band power during operation of an ERP (P300) brain-computer interface. Biological Psychology, 102(October), 118-129. https://doi.org/10.1016/j.biopsycho.2014.07.014
Klimesch, W., Schack, B., & Sauseng, P. (2005). The functional significance of theta and upper alpha oscillations. Experimental Psychology, 52(2), 99-108. https://doi.org/10.1027/1618-3169.52.2.99
Knoll, A., Wang, Y., Chen, F., Xu, J., Ruiz, N., Epps, J., & Zarjam, P. (2011). Measuring cognitive workload with low-cost electroencephalograph. In IFIP Conference on Human-Computer Interaction (pp.568-571).
Mallick, Z., Badruddin, I. A., Haleem, A., Siddique, A. N., & Tandur, K. H. (2007). Ergonomic evaluation of data entry task performance under the influence of noise and task structurce - The effect of gender. International Journal of Mechanical and Materials Engineering, 2(2), 161-172.
Matthews, G., Reinerman-Jones, L. E., Barber, D. J., & Abich, J. (2015). The psychometrics of mental workload: Multiple measures are sensitive but divergent. Human Factors, 57(1), 125-143. https://doi.org/10.1177/0018720814539505
Mazloum, A., Kumashiro, M., Izumi, H., & Higuchi, Y. (2008). Quantitative overload: A source of stress in data-entry VDT work induced by time pressure and work difficulty. Industrial Health, 46(3), 269-280. https://doi.org/10.2486/indhealth.46.269
Mcmahan, T., Parberry, I., & Parsons, T. D. (2015). Modality specific assessment of video game player’s experience using the Emotiv. Entertainment Computing, 7(March), 1-6. https://doi.org/10.1016/j.entcom.2015.03.001
Mehta, R. K. (2016). Integrating physical and cognitive ergonomics. IIE Transactions on Occupational Ergonomics and Human Factors, 4(2-3), 83-87. https://doi.org/10.1080/21577323.2016.1207475
Mercado, J. E., Reinerman-Jones, L., Barber, D., & Leis, R. (2014). Investigating workload measures in the nuclear domain. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 58(1), 205-209. https://doi.org/10.1177/1541931214581043
Nachreiner, F. (1999). International standards on mental work-load. Industrial Health, 37(2), 125-133. https://doi.org/10.2486/indhealth.37.125
Oladimeji, P., Thimbleby, H., & Cox, A. (2011). Number entry interfaces and their effects on error detection. In IFIP Conference on Human-Computer Interaction (pp. 178-185).
Wiseman, S., Borghouts, J., Grgic, D., Brumby, D. P., & Cox, A. L. (2015). The effect of interface type on visual error checking behavior. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 59(1), 436-439.
Young, M. S., Brookhuis, K. A., Wickens, C. D., & Hancock, P. A. (2015). State of science: Mental workload in ergonomics. Ergonomics, 58(1), 1-17. https://doi.org/10.1080/00140139.2014.956151
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