Optimizing DBSCAN Parameters for Depth-Based Earthquake Clustering Using Grid Search

Optimizing DBSCAN Parameters for Depth-Based Earthquake Clustering Using Grid Search

clustering; DBSCAN; earthquake data; grid search; Sulawesi; seismic gap

This study addresses the challenge of accurately clustering earthquake events based on depth to better understand seismic activity patterns in Sulawesi from 2019 to 2023. Traditional clustering algorithms often fail to capture the complex spatial and depth-based structures of earthquake data. To overcome this, we employed the DBSCAN algorithm, which is well-suited for identifying irregularlyshaped clusters and handling noise in spatial datasets. A key focus of this research is the systematic optimization of DBSCAN’s parameters—epsilon (ε) and minimum samples (min_samples)—using a grid search approach. Epsilon values varied from 0.1 to 0.5, and min_samples ranged from 6 to 60. The optimal parameters, determined using the Calinski-Harabasz (CH) index, were ε = 0.4 and min_samples = 54. Compared with previous heuristic settings, the optimized configuration produced better separated and more interpretable clusters. Using the optimized parameters, nine distinct clusters were identified, capturing meaningful patterns in both depth and magnitude. The results revealed that shallow earthquakes (0–20 km) tend to exhibit greater magnitude variation, withsome clusters averaging magnitudes up to 3.7. This suggests a higher seismic hazard potential associated with brittle crustal activity. The findings contribute to seismic hazard analysis by providing a more robust understanding of three-dimensional earthquake distribution, aiding regional risk assessment and disaster preparedness efforts. These insights can support agencies such as BMKG and BPBD in hazard mapping, sensor deployment, and contingency planning for high-risk zones.

Rushendra1*, Ody Octora Wijaya2, Mohamad Yusuf3, Andri Setiyaji4, Djoko Prabowo5

https://jurnal.iaii.or.id/index.php/RESTI/article/view/6521/1117

Department of Informatics, Universitas Mercu Buana, Jakarta, Indonesia

August 19, 2025

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