Abstract
The rapid growth of information and communication technology has also reached the transportation sector, especially in Indonesia. Railway locomotives have experienced significant advancements by transitioning from conventional systems to the use of microcontroller-based sensors. However, to expedite repairs, swift identification of faults is necessary. Railway workers need to continuously improve the quality of human resources and develop application systems to facilitate technicians in identifying issues with CC 201 locomotives. The aim of this research is to build a system that can identify faults and facilitate technicians in diagnosing and providing repair solutions for CC 201 locomotives, using the Case-Based Reasoning method. Research results indicate that this system can be used to diagnose CC 201 locomotive issues based on observed symptoms. Usability testing for 20 respondents using the SUPR-Q method shows an excellent level of system ease and satisfaction, with a score of 90.86%.
Published Version
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