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Journal : Jurnal Geosaintek

SEISMIC SITE QUALITY ASSESSMENT IN NORTH SUMATRA USING SPECTRAL DENSITY ANALYSIS AND MACHINE LEARNING-BASED CLUSTERING Triya Fachriyeni; Katherin Indriawati; Kevin W. Pakpahan; Irfan Rifani; Anne M. M. Sirait; Yusran Asnawi; Hendro Nugroho; Andrean V. H. Simanjuntak
Jurnal Geosaintek Vol. 11 No. 3 (2025)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25023659.v11i3.8972

Abstract

Seismic noise strongly influences the accuracy and reliability of earthquake monitoring, particularly in tectonically active regions such as North Sumatra. This study investigates the quality of seismic stations by analyzing noise characteristics using Power Spectral Density (PSD), Probability Density Functions (PDFs), and machine learning clustering. PSD was computed through the Fast Fourier Transform (FFT) and compared against the New High Noise Model (NHNM) and New Low Noise Model (NLNM) benchmarks. Noise variability was further quantified using PDFs, while fuzzy c-means (FCM) clustering was applied to classify temporal noise patterns. Results from the MUTSI seismic station demonstrate strong diurnal and weekly variability, with horizontal components (SHE and SHN) exhibiting significantly higher noise levels and fluctuations than the vertical component (SHZ). Noise amplitudes peaked during morning hours (06:00–09:00 UTC), correlating with anthropogenic activity, and decreased substantially at night, indicating that optimal recording conditions occur during late evening to early morning. FCM clustering identified five dominant noise regimes, separating stable low-noise baselines from sporadic high-noise anomalies likely associated with human activity or instrumental disturbances. These findings highlight the importance of integrating spectral analysis with clustering techniques to evaluate seismic station performance, improve real-time monitoring, and guide optimal site selection and operational scheduling for earthquake detection.
IDENTIFIKASI MISORIENTATION SENSOR SEISMOGRAF BMKG MENGGUNAKAN METODE P-WAVE PARTICLE MOTION: STUDI DI PULAU SUMATERA BAGIAN UTARA Chichi Nurhafizah; Purwadi Agus Darwito; Wijayanto Wijayanto; Hendro Nugroho
Jurnal Geosaintek Vol. 11 No. 3 (2025)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25023659.v11i3.8974

Abstract

Analisis polaritas gelombang P dapat digunakan untuk mengevaluasi keakuratan orientasi sensor seismograf. Ketidaktepatan orientasi (misorientation) berpotensi menurunkan akurasi penentuan mekanisme sumber gempa bumi. Penelitian ini menganalisis orientasi sensor seismograf BMKG di wilayah Sumatera bagian utara dengan menggunakan metode P-Wave Particle Motion. Sebanyak 58 sensor berhasil dianalisis secara kuantitatif dan menghasilkan estimasi sudut orientasi aktual. Hasil menunjukkan bahwa sensor memiliki variasi misorientation berkisar antara 1° hingga 46°, dengan 15 sensor di antaranya menunjukkan nilai misorientation signifikan, yaitu RSSM (46°), MASM (28°), PAASI (27°), SLSM (24°), TPTI (23°), GESM dan SKSI (22°), TKSM dan BESM (20°), SMSM (19°), LTSM dan TASI (18°), PDSI (17°), serta PLSI dan KASAI (16°). Temuan ini menunjukkan ketidaksesuaian arah pemasangan sensor terhadap arah utara sejati, yang dapat menurunkan kualitas interpretasi data seismik, sehingga evaluas misorientation sensor berbasis data perlu dilakukan secara berkala guna menjaga reliabilitas data seismik nasional. Penelitian ini merupakan evaluasi sistematis berskala besar pertama terhadap orientasi sensor BMKG di Indonesia dengan memanfaatkan analisis gerak partikel gelombang teleseismik, sehingga memberikan dasar ilmiah penting bagi pengembangan standar kualitas jaringan seismograf di masa mendatang.
SEISMOTECTONIC STUDY OF THE SIBOLANGIT, NORTH SUMATRA REGION BASED ON DOUBLE-DIFFERENCE RELOCATION Nesia S. Marbun; Aulia A. Aisjah; Anne M. M. Sirait; Yusran Asnawi; Hendro Nugroho; Andrean V. H. Simanjuntak
Jurnal Geosaintek Vol. 11 No. 3 (2025)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25023659.v11i3.8986

Abstract

Sumatra is one of the most seismically active regions in the world due to the oblique convergence between the Indo-Australian and Eurasian plates, where strain is partitioned between the Sunda megathrust and the Great Sumatran Fault (GSF). While most seismicity in North Sumatra occurs along mapped strands of the GSF, several damaging earthquakes have occurred outside known fault zones, raising critical questions about hidden seismogenic structures. This study investigates the seismotectonic framework of the Karo region, with a focus on the 2017 Karo earthquake (Mw 5.6), using the double-difference relocation method. A dataset of local earthquakes recorded by the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) was analyzed to refine hypocenter locations, reduce uncertainties, and identify seismic clusters. Relocation results significantly improved spatial resolution, reducing average location errors to less than 3 km, and revealed clustered seismicity along a northwest–southeast trending structure offset from the Renun Fault. Depth cross-sections indicate brittle faulting within the upper crust (5–12 km), and the aftershock alignment suggests the presence of an unmapped subsidiary fault accommodating dextral shear. Comparisons with similar studies across Sumatra and Java confirm that off-fault seismicity is a common but often overlooked contributor to regional hazard. These findings underscore the importance of integrating relocated seismicity into national hazard models to account for hidden faults. By providing improved fault geometry and seismotectonic insights, this study enhances the understanding of earthquake sources in North Sumatra and supports future efforts in seismic hazard mitigation and disaster risk reduction in one of Indonesia’s most vulnerable regions.