VALIDATION OF FATIGUE AND RISK INDEX CALCULATOR BASED ON DATA OF INDONESIAN MACHINISTS WORK PROFILE

• Main Author: Nursagita, Chicha
• Format: Theses
• Language: Indonesia
• Subjects: Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
• Online Access: https://digilib.itb.ac.id/gdl/view/76215
• Institution: Institut Teknologi Bandung

Train accidents often occur in Indonesia, developing countries and even in the world. One of the factors that caused the train accident was the human factor, namely driver fatigue. There are many methods or tools for identifying fatigue, one of which is the Fatigue and Risk Idex Calculator (FRIC), but its validation is uncertain. The purpose of this study was to evaluate the Fatigue and Risk Idex Calculator (FRIC) as a tool that can be used to identify adequate fatigue in train drivers at Division IV Regional PT. Indonesian Railways (KAI). The research results are expected to be utilized by PT KAI to later be implemented in all Operational Areas and Regional Divisions (DivRe) in establishing policies related to fatigue management before machinists travel on business so as to improve their job performance. The method used in this study is to compare the results of fatigue measurements on FRIC with subjective and objective measurement results. Subjective measurements include the results of evaluation questionnaires and fatigue identification questionnaires (Karolinska Sleepiness Scale (KSS) and Visual Analogue Scale (VAS) and NASA-TLX). While objective measurements include measurements of the Sustained Attention Test (SAT) and Blink Duration (BD). Statistical analysis was carried out, namely standardization, normality test, Friedman twoway ANOVA test, Wilcoxon Signed Ranks test and Spearman correlation test. The results showed that the Fatigue and Risk Index Calculator had differences with all subjective and objective measurement methods, but there were no differences with the Initial VAS. In the correlation test, there was only a correlation with shifts, work duration, commuting time and chronic illness. Where shifts, work duration and commuting time are the input variables in FRIC, while there is no correlation with other fatigue factors. Therefore it can be concluded that the FRIC validation value is low. This might happen because the variables in FRIC only cover a small number of fatigue factors, even though there are many other fatigue factors that might contribute. So a model is proposed in the identification of fatigue in FRIC but further tests and research are needed to realize this.