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This study assesses seismic site quality in North Sumatra by analyzing seismic noise characteristics using Power Spectral Density (PSD) and machine learning clustering techniques. The results reveal significant diurnal and weekly variability in noise levels, with higher noise during morning hours linked to human activities, and identify five dominant noise regimes. The findings emphasize the integration of spectral analysis and clustering for improved earthquake monitoring and site selection.

Author

akhmadisuryanata17

Language

EN