PENENTUAN NILAI AMBANG BATAS BEBAN KERJA MENTAL MENGGUNAKAN GALVANIC SKIN RESPONSE (GSR)

Mental workload needs to be considered in the process of optimizing a system because it significantly affects human performance. One tool to measure mental workload that has proven its sensitivity is Galvanic Skin Response (GSR). Although GSR is sensitive, it does not yet have secure criteria for...

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Bibliographic Details
Main Author: Ardinta, Davina
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/74416
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Mental workload needs to be considered in the process of optimizing a system because it significantly affects human performance. One tool to measure mental workload that has proven its sensitivity is Galvanic Skin Response (GSR). Although GSR is sensitive, it does not yet have secure criteria for measurement results. Therefore, this research aims to determine the threshold values for measuring mental workload using GSR. The determination of threshold values is based on experimental results involving 50 participants. The experiment involved assigning tasks to the participants and measuring their mental workload. Three types of tasks were used: search, change blindness, and counting tasks. The measurement of mental workload was conducted using a multimethod approach, utilizing performance data, NASA-TLX scores, and GSR measurements. The experimental data was processed using ANOVA and Fisher's LSD test. The established threshold values consist of two variables, namely skin conductance level (SCL) and skin conductance response amplitude (SCR). The threshold value for SCL and SCR amplitude is a 28% increase in SCL compared to an individual’s baseline condition and 5 SCR/minute. Spearman correlation analysis was performed to determine the appropriate use of the threshold values. The Spearman correlation coefficient indicates a weak relationship between SCL values and SCR amplitude. The weak relationship between these two variables emphasizes the need to consider both variables in measuring mental workload.