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All Journal Journal of Geoscience, Engineering, Environment, and Technology Jurnal Geosaintek
Andrean V. H. Simanjuntak
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Earth & Planetary Sciences Engineering Environmental Science Physics

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Experimental of Environmental Development Using Continuous Solar Dryer With Solid Dehumidification For Coffee Drying Parulian Siagian; Aprima A. Matondang; Andreas V. H. Simanjuntak; Budhi S. Kusuma; Joel Panjaitan; Andrean V. H. Simanjuntak
Journal of Geoscience, Engineering, Environment, and Technology Vol. 10 No. 02 (2025): JGEET Vol 10 No 02 : June (2025)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2025.10.02.21492

Abstract

As the tropical country, Indonesia has a sustainable solar energy for the farm products such as coffee. Indonesia’s coffee has been categorized as one of the biggest export products in the world and needs a development system to provide drying coffee beans with good quality. Therefore, this study comprehensively explains an experiment to develop a continuous solar air dryer with a hybrid system for drying coffee. The system has two different modes: off-sunny and sunshine hours. The heated air from the collector is driven into the drying chamber during the sunlight. The results show that the drying chamber's maximum temperature during daylight ranged from 40°C to 56°C and 9°C to 22°C warmer than the ideal environment temperature. Then, the coffee beans got the 12,7% moisture content in 107 hours in a solar dryer with solid dehumidification material. During off-sunlight, the air humidity reaches a 17% reduction and relatively consistent with air temperature. Furthermore, the benefit of this research can support the agricultural system without sunlight and apply a molecular sieve as a solar dehumidifier for the desiccant material in the drying chamber.
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.
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.
Co-Authors Andreas V. H. Simanjuntak Anne M. M. Sirait Aulia A. Aisjah Baehaqi Budhi S. Kusuma Hendro Nugroho Irfan Rifani Joel Panjaitan Katherin Indriawati Kevin W. Pakpahan Nesia S. Marbun Parulian Siagian Triya Fachriyeni Yusran Asnawi