Purpose This study aims to develop and validate a decision support system for diesel generator maintenance at KM. Bukit Siguntang through identifying critical parameters that affect maintenance needs, analyzing failure patterns and reliability levels of key components, and implementing a validated model to optimize maintenance strategies based on actual engine conditions. Methodology This study uses a mixed-method approach with a combination of quantitative and qualitative methods. The research design is exploratory sequential mixed-method, which begins with a qualitative stage to identify parameters and decision-making criteria, followed by a quantitative stage for model development and system validation. The collected data were analyzed using the Descriptive Statistical Analysis method, Reliability Centered Maintenance (RCM) Analysis. Findings The results showed a decrease in the number of unplanned failures by 57.1% and a reduction in downtime by 53.8% indicating a substantial increase in system reliability. This contributed to an increase in diesel generator availability from 94.2% to 97.3%, which is very important for ship operations. Originality This study successfully developed and validated a decision support system for diesel generator maintenance at KM. Bukit Siguntang by identifying 11 critical parameters that affect maintenance needs and analyzing failure patterns and reliability of critical components.