Decision Support System Assessment Of Truck Driver Work Mental Load in Giwangan Market Area, Yogyakarta Using NASA-TLX
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Summary
This study addresses the high mental workload experienced by truck drivers operating in the Giwangan Market area of Yogyakarta, Indonesia. The research is motivated by the decline in traditional market performance and the inadequate infrastructure of these markets, which contributes to driver fatigue. Driver fatigue is a significant safety concern, cited as a cause for 30% of road accidents. To mitigate this, the authors developed a Decision Support System (DSS) to assess and visualize the mental workload of truck drivers, providing market managers with data to improve operational conditions and driver safety. The methodology employed a case study approach focusing on truck drivers working in the Giwangan Market area. The researchers utilized the NASA-TLX (Task Load Index) subjective scale to measure mental workload. This method requires participants to rate six specific sub-scales: mental demand, physical demand, temporal demand, performance, effort, and frustration level. The DSS was designed to facilitate data input, perform pairwise comparisons to determine indicator weights, calculate the weighted workload score, and interpret the results. The system’s interface was designed to display accurate information and integrated subsystems for detailed reporting. Data was collected from 10 truck drivers who frequently entered the market area. The NASA-TLX scores were calculated by multiplying the ratings by the weighted factors for each indicator and dividing by the total weight. The results indicated a high average mental workload, with a mean Rounded TLX score of 73.83. Specifically, four drivers exhibited "very high" mental workload (scores 80–100), five showed "high" workload (scores 50–79), and one showed "moderately high" workload (score 46). Mental Demand was the most significant contributor to the workload (average score 290.3), followed by Effort (277) and Performance (200.2). Frustration Level had the lowest impact (average score 9). The high mental demand was attributed to the need for constant perceptual attention to navigate the market and find unloading spaces. High temporal demand resulted from the urgency to deliver perishable goods quickly, while high effort was driven by the need to minimize operational costs despite poor road conditions. The study concludes that the developed DSS accurately assesses mental workload in accordance with NASA-TLX interpretations. The system’s user interface effectively meets data processing needs and displays integrated, detailed information. The findings highlight that truck drivers in this environment face significant cognitive and physical pressures, primarily due to mental demands and time constraints. The DSS serves as a tool for market managers to understand these stressors, potentially informing interventions to reduce fatigue and improve safety.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| enrich | failed | — | — | — | 1 | 2026-08-09 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 10 | 2026-08-11 |
| verify | partial | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified_with_issues.
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