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All Journal Jurnal Geosaintek Journal of Computation Physics and Earth Science
Triya Fachriyeni
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Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Physics

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Active Tectonic Segmentation on the Micro Plate of Northern Sumatra Based on Distribution of Earthquake Epicenter in July 2020 Nesia Sabrina Marbun; Melda Panjaitan; Triya Fachriyeni; Eridawati
Journal of Computation Physics and Earth Science (JoCPES) Vol 1 No 2 (2021): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v1i2.01

Abstract

The main goal of this study to increase awareness of earthquake activity due to local faults that have so far received "less attention". Continuous observations can be made on site (on active faults), by using portable seismographs and/or by utilizing the Indonesia Tsunami Early Warning System (Ina-TEWS) network broadband sensors adjacent to these active faults. However, observing using a Portable Seismograph for a long period of time will certainly require a large amount of money. Therefore, it will be more effective to utilize data from seismic sensors that are relatively close to the suspected faults. Based on the analysis that has been carried out, it can be concluded that, in the period from July 1, 2020 to July 31, 2020, there have been 79 earthquakes in the North Sumatra region, with magnitudes between 2.0 – 5.2. The location of the earthquake was dominated by land earthquakes with shallow depths, namely 0-60 km with 54 events and at sea 25 occurrences. The most earthquake occurrences in the period 01 July 2020 - 31 July 2020 occurred around Cluster 1 (local fault Aceh Central, Batee-A, Aceh South, Pidie Jaya and Lot Aceh North, Seulimeum-South), namely 15 earthquake events, so it is classified as a cluster. which is very active in the July 2020 period. In the July 2020 period, seismic activity around the Tripa 2 and Oreng local faults was low compared to other local faults in Northern Sumatra, while in June 2020 there was no seismic activity around the Tripa local faults. 2, and the Oreng fault.
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.
Co-Authors Andrean V. H. Simanjuntak Anne M. M. Sirait Eridawati Hendro Nugroho irfan rifani Katherin Indriawati Kevin W. Pakpahan Melda Panjaitan Nesia Sabrina Marbun Yusran Asnawi