Citation

Sudiarno A, Ma'arij AMD, Tama IP, Larasati A, Hardiningtyas D. Automot. Exp. 2023; 6(1): 149-161.

Copyright

(Copyright © 2023, Universitas Muhammadiyah Magelang)

DOI

10.31603/ae.8301

PMID

unavailable

Abstract

As part of the Supply Chain (SC), oftentimes Land Logistic Driver (LLD) are held by various uncontrollable occurrences from the surroundings. This caused the cognitive load of the drivers to become higher, which could potentially affect the performance of the LLD to meet the Key Performance Indicator (KPI) of the SC overall. Not only the performance that is affected, but a higher load also could affect the driving behavior towards negativity, as anger and stress perceived become higher, hence a higher crash possibility. Therefore, the need to study the possibility to measure the cognitive load in a certain route that they are on, so any adjustments could be made during a transport activity, with Electroencephalogram (EEG) used as the means to measure it. This study is done by reviewing 15 available research as references regarding EEG and cognitive load. It is possible to use EEG in measuring cognitive load during driving activity, with the focus area of data gathering on the central lobe, parietal lobe, and temporal lobes, with the data extracted from EEG should use the most accurate classifier that focuses on analyzing beta (β) and alpha (α) band as the significant brain wave of the active state. The possible result of the brain wave analysis could be used to determine whether the current route option is burdening LLDs' cognitive load and should be corrected to improve safety driving. Further inclusion of the analysis result could be incorporated into a set of KPI in measuring SC performance.

Language: en