Hielmy, Rayhan Irfan
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ANALISIS PROBABILISTIK BAHAYA SEISMIK DI DENPASAR DAN SEKITARNYA BERDASARKAN PENDEKATAN PSHA Hielmy, Rayhan Irfan; Rajagukguk, Martha Lisauli
JOURNAL ONLINE OF PHYSICS Vol. 11 No. 1 (2025): JOP (Journal Online of Physics) Vol 11 No 1
Publisher : Prodi Fisika FST UNJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jop.v11i1.47825

Abstract

Indonesia berada di wilayah dengan aktivitas seismik tinggi akibat pertemuan tiga lempeng tektonik utama, menjadikannya rawan gempa, termasuk Kota Denpasar yang berdekatan dengan Subduksi Sunda, Flores Back Arc Thrust, dan Sesar Lombok. Penelitian ini menganalisis bahaya seismik di Denpasar menggunakan metode Probabilistic Seismic Hazard Analysis (PSHA) dengan perangkat OpenQuake Engine dari Global Earthquake Model. Perhitungan menghasilkan nilai percepatan tanah maksimum (PGA) dan percepatan spektral (SA) pada periode 0,2 s dan 1 s, dengan periode ulang 50 tahun untuk Probability of Exceedance 2%, 5%, dan 10%. Hasil menunjukkan PGA untuk Probability of Exceedance 2%, 5%, dan 10% berturut-turut berkisar 0,474–0,483 gal, 0,344–0,349 gal, dan 0,265–0,269 gal. SA 0,2 s masing-masing 1,094–1,123 gal, 0,769–0,782 gal, dan 0,575–0,583 gal, sedangkan SA 1 s berkisar 0,278–0,285 gal, 0,197–0,200 gal, dan 0,146–0,148 gal. Nilai tertinggi terletak di Denpasar Selatan karena lokasinya yang dekat dengan zona subduksi, sedangkan terendah di Denpasar Timur, Utara, dan Barat. Hasil ini dapat menjadi acuan perencanaan tata ruang, desain bangunan tahan gempa, dan strategi mitigasi bencana.
Performance Evaluation of Automated and Manual Seismic Phase Picking for Rapid Earthquake Parameter Determination in the Indonesian BMKG Network Hielmy, Rayhan Irfan; Pranata, Bayu; Wijayanto; Daryono
Jurnal Meteorologi dan Geofisika Vol. 26 No. 2 (2025)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v26i2.1189

Abstract

Indonesia is situated at the intersection of three major tectonic plates, resulting in high seismic activity and significant earthquake vulnerability.1 Rapidly determining initial earthquake parameters—including origin time, epicenter location, depth, and magnitude—is critical for effective early warning systems. This study evaluates the reliability of automated versus fast manual picking (<3 minutes, S-wave-based) by comparing their performance against final validated results. Utilizing data from the BMKG SeisComP system for the period of May 18, 2024, to May 17, 2025, the study analyzed 2,790 seismic events across Indonesia, including low-seismicity regions such as Kalimantan. Performance was assessed across six key parameters (depth, origin time, RMS, azimuth gap, magnitude, and epicenter) using a numerical scoring system (0–100) based on deviation from validated data. The results indicate that while automated picking processed a significantly higher volume of events (1,857 events; 66.6%) compared to manual picking (327 events; 11.7%) within the target timeframe, manual picking achieved a superior 'good' quality rating (score 75–100) at 96.9%, compared to 88.5% for automated methods. Nevertheless, automated picking remains the preferred method for rapid dissemination (<3 minutes) due to its operational speed. Furthermore, the study establishes regional thresholds for the minimum seismic phases required for reliable automated picking, ranging from 8 to 16 phases depending on the region, with a national average of 15 phases.