<![CDATA[This study aims to develop a web-based worker clustering system at Disnaker Perindag Binjai City using the Fuzzy C-Means (FCM) method. Data from 387 registered workers between 2022–2025 were processed based on age, education, work experience, expertise, and certifications. Data processing steps included cleaning, normalization, and clustering with parameters (c)=4, (m)=2, (ε) =0,0001, and a 100-iteration limit. The system classifies workers into four groups based on work readiness and competence. Implemented using Python, Flask, and SQLite, the web application features data management, automated clustering, and result visualization. Evaluation using the Silhouette Coefficient demonstrates that FCM effectively clusters workers into four groups with a balanced distribution and high clustering performance. This system is expected to support more structured workforce management.]]>
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