A Multidimensional Framework for Night Shift Train Operator Readiness

Fina Zaimah Maznah

doi:10.33506/mt.v10i1.3125

Authors

Fina Zaimah Maznah Universitas Esa Unggul

DOI:

https://doi.org/10.33506/mt.v10i1.3125

Keywords:

cluster analysis, factor analysis, fitness for duty, sleepiness, stress

Abstract

Machinists who work the night shift experience a higher probability of sleepiness. The intricate relationship between sleepiness, fatigue, and stress has been acknowledged, especially considering that a significant 75% of accidents stem from drivers who are fatigued. The purpose of this study is to identify the factors that influence fitness for duty. The methods used are factor analysis and cluster analysis. The results of factor analysis show that from the 7 initial variables studied can be reduced to 4 factors in which represent the 7 initial variables. These factors consist of fatigue factor, age factor, physical factor and stress level factor. The unexpected discovery emerges that sleepiness, a presumed influencing factor, does not align with the anticipated impact on fitness for duty, as per existing theoretical frameworks. This study contributes to a nuanced understanding of the multifaceted interplay between variables affecting fitness for duty among night shift machinists. The unanticipated findings prompt further exploration, thereby fostering a more comprehensive comprehension of the intricate dynamics at play in occupational settings.

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