Abstract
As a mode of mass transportation, trains are one of the choices for people to travel. Safety and security of train travel are important factors in the implementation of railway transportation. One of the problems in railways is the low safety performance reflected by the high number of accidents. Machinists play an important role in the safety of railroad trave. The increasing number of schedules and trips as well as the lack of the number of machinists assigned to Divre II West Sumatra resulted in an increasingly dense schedule arrangement that affects the workload and mental burden felt by machinists and of course will also have an impact on the safety of the train journey itself. Therefore, it is necessary to conduct research on workload and mental load on machinists. This study aims to predicting the probability of train accidents in terms of factors affecting the level of fatigue, predicting the probability of train accidents in terms of factors affecting workload and mental load, analyzing the relationship between factors affecting workload and mental load felt by machinists in relation to train accidents. The method using modeling with a Bayesian Network Structure (SBN) using questionnaire data conducted on machinists in Divre II West Sumatera which is then analyzed using Gennie 2.2 Software to obtain the probability value of accidents that may occur to machinists based on the machinist classification level and finally find out what factors affect the workload and mental of machinists.
Published Version
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