MANPOWER PLANNING FOR TRAIN DRIVER USING MENTAL WORKLOAD EVALUATION CASE STUDY AT UPT CREW KERETA API TANJUNGENIM BARU PT KERETA API INDONESIA (PERSERO)
PT Kereta Api Indonesia (Persero) faces financial losses due to declining passenger and freight revenues during the pandemic. However, freight rail transportation has grown, requiring additional machinists to support efficient operations. Challenges with driver training, certification, and the uncer...
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| Format: | Theses |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/80769 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | PT Kereta Api Indonesia (Persero) faces financial losses due to declining passenger and freight revenues during the pandemic. However, freight rail transportation has grown, requiring additional machinists to support efficient operations. Challenges with driver training, certification, and the uncertainty of freight train schedules cause drivers to work overtime. Overtime can increase fatigue, stress, and the risk of accidents, which can affect performance and result in losses for the company. To address the problem, this research uses the RNASA-TLX technique to measure mental workload and determine the necessary number of machinists, adjusting based on workload assessment.
This study analyzed the mental workload of 181 train drivers at the Tanjungenim Baru Railway Crew Unit. The average RNASA-TLX score of 61.03 indicates a moderate mental workload for train drivers, which suggests that their working conditions and overtime demands are manageable. Among the respondents, 52 reported low mental workload, 87 reported moderate, and 42 reported high mental workloads. A low mental workload can cause a decrease in productivity and work performance, thus increasing human error. Companies should improve competencies, implement workplace rotation strategies, and provide constructive feedback to optimize the mental workload. The high mental workload can negatively impact performance, errors and stress, requiring monitoring, coaching and mentoring to help train drivers to manage their workload. Based on PT KAI's method, the number of train drivers needed at the time of the study was 196, resulting in a moderate mental workload of 56.36. Based on this finding, PT KAI can use its method to plan the number of machinists to maximize current and future opportunities.
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