<![CDATA[Work productivity and employee well-being are critical aspects of organizational management, particularly at PT XYZ. The Administrative and Operational Support Division faces ergonomic challenges due to prolonged sitting in non-ergonomic positions. This study aims to analyze ergonomic risks using the Nordic Body Map (NBM) combined with Fuzzy Logic. Traditional ergonomic methods are often manual and subjective. NBM is applied to map employees' physical complaints based on body areas, while Fuzzy Logic is utilized to classify risk levels with higher precision. Data reveal that lower back and neck complaints dominate moderate to high-risk levels, affecting overall work efficiency. The results demonstrate that implementing Fuzzy Logic improves evaluation accuracy by up to 20% compared to traditional methods. Furthermore, this approach provides data-driven recommendations for ergonomic interventions, including workstation adjustments and posture training programs. This study not only offers practical solutions for PT XYZ but also expands the application of Fuzzy Logic technology in ergonomic analysis. It highlights the significant potential for reducing ergonomic risks and serves as a reference for other organizations aiming to develop data-driven ergonomic strategies to enhance work productivity and employee well-being.]]>
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