<![CDATA[This research aims to develop and implement an integrated data processing system based on KNIME to analyze employee satisfaction at X School. The methodology involved collecting data via a survey distributed to 125 employees, integrating data from Google Sheets, preparing the data, applying the K-Means algorithm to cluster employees by satisfaction levels, and visualizing the results in an interactive dashboard. The research results indicate that the system was successfully built and can group employees into three clusters: Very Satisfied, Satisfied, and Less Satisfied. User acceptance testing (UAT) showed that the system met 80% of the testing criteria, indicating that most features functioned as expected by users. Evaluation using the Silhouette Coefficient produced an average value of 0.19, indicating less-than-optimal clustering quality, but the system still provided an overview of employee satisfaction levels. This system supports KNIME use for employee satisfaction analysis and provides strategic recommendations for X School to improve employee satisfaction and retention.]]>
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