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Muh. Altin Massinai
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Departemen Geofisika, Fakultas Matematika dan Ilmu Pengetahuan Alam - Universitas Hasanuddin, Gedung MIPA, Kampus Unhas Tamalanrea - Jalan Perintis Kemerdekaan, Makassar - Sulawesi Selatan 90245
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Jurnal Geocelebes
Published by Universitas Hasanuddin
ISSN : 25795821     EISSN : 25795546     DOI : https://doi.org/10.20956/geocelebes.vxix.xxxxx
Core Subject : Science,
Earth & Planetary Sciences
Jurnal Geocelebes adalah jurnal peer-review yang dipublikasikan oleh Departemen Geofisika Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Hasanuddin. Jurnal ini terbit dua kali dalam setahun pada bulan April dan Oktober. Jurnal ini diperuntukkan sebagai sarana publikasi ilmiah di bidang geofisika baik teoritik maupun terapan. Artikel yang dimuat merupakan hasil penelitian yang orisinal, tinjauan (review) tentang kemajuan terkini dari suatu topik tertentu, studi kasus aplikasi geofisika atau pun resensi tentang perangkat lunak yang berkaitan dengan geofisika. Fokus dan cakupan topik yang dimuat dalam Jurnal Geocelebes: Geofisika eksplorasi Seismologi Vulkanologi Geofisika lingkungan Hidrometeorologi Oseanografi Dinamika pantai dan lautan Geoinformatika Mitigasi bencana geologi
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Geofisika
Articles 7 Documents
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Search results for , issue "Vol. 10 No. 1: April 2026" : 7 Documents clear
The Earthquake Prediction in the Southern Part of Sumatra Using Deep Learning (Long Short-Term Memory) Models Ainul Lisa; Refrizon, Refrizon; Samdara, Rida
JURNAL GEOCELEBES Vol. 10 No. 1: April 2026
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v10i1.42958

Abstract

The Southern part of Sumatra is highly vulnerable to earthquakes due to its location in the subduction zone between the Indo-Australian plate and the Sunda plate. The Southern part of Sumatra’s vulnerability to earthquakes poses significant risks. This research aims at predicting the Earthquakes in the Southern part of Sumatra Using Deep Learning (Long Short-Term Memory) Models, a deep learning method designed to analyze sequential data. The model utilized 20 years of historical earthquake data from 2004 to 2024, with parameters including magnitude, epicenter location, depth, and event time. Data were preprocessed using Min-Max Scaling normalization and split into training data (70%) and testing data (30%). The model was trained over 150 epochs with a batch size of 32. Evaluation results showed a Mean Absolute Error (MAE) of 0.28 and a Root Mean Squared Error (RMSE) of 0.39, indicating high prediction accuracy. The distribution of prediction results confirmed previous studies indicating that earthquakes in Southern part of Sumatra frequently occur in Bengkulu, western South Sumatra, and Southwestern Lampung. These findings underscore the importance of ongoing seismic hazard mitigation efforts and sustainable development planning in earthquake-prone areas.
Analysis of Extreme Weather in the Waters of West Kalimantan using the WRF-ARW Model (Case Study 13-14 July 2021) Juliana, Tarisya; Adriat, Riza; Ardianto, Randy; Ihwan, Andi; Sutanto, Yuris
JURNAL GEOCELEBES Vol. 10 No. 1: April 2026
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v10i1.43141

Abstract

On 13 July 2021, there was an extreme weather phenomenon in the waters of West Kalimantan. The extreme weather resulted in several fishing boats sinking and causing 136 casualties. This study aims to analyze atmospheric conditions during extreme weather on July 13-14, 2021. In running the WRF-ARW model, verification is carried out using the dichotomy method (Accuracy, POD, FAR) and RMSE to determine the model's accuracy in simulating extreme weather events. The RMSE verification results show an error value of 4,97. The results of the WRF-ARW model output show that the extreme weather that occurs is caused by the presence of a convergence wind zone with a maximum wind speed of 18 m/s, causing the formation of cumulonimbus clouds. OLR simulations show a low value of 122 watts/m², indicating a lot of cloud cover with the potential for rain. The emergence of this convection zone causes strong winds, which cause high waves, thus contributing to ship accidents.
Comparative Accuracy of Satellite-Derived Bathymetry Using Random Forest, Multiple Linear Regression, and Van Hengel and Spitzer Algorithm Apriliansyah, Fathurrahman; Nuha, Muhammad Ulin; Atmojo, Aulia Try; Setiawan, Kuncoro Teguh; Syafnur, Aswar
JURNAL GEOCELEBES Vol. 10 No. 1: April 2026
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v10i1.43582

Abstract

Bathymetry mapping using conventional methods faces limitations in shallow waters. With the development of remote sensing technology, satellite-derived bathymetry (SDB) emerges as an alternative by utilizing wavelengths that penetrate water and capture depth information. This study compares the performance of three empirical SDB methods: Random Forest (RF), Multiple Linear Regression (MLR), and the Van Hengel and Spitzer (VHS) algorithm. SPOT 6 ORTHO-level satellite imagery and depth data from single beam echosounder measurements were used to construct the depth models. Model accuracy was evaluated using root mean square error (RMSE), mean absolute error (MAE), and total vertical uncertainty (TVU). Results show that the RF method achieves the highest accuracy across most depth ranges (1–5 m, 5–10 m, and 10–15 m), while the VHS algorithm performs best at 0–1 m. At depths beyond 15 meters, MLR shows relatively better performance compared to other methods, although overall uncertainty remains high. Based on the coefficient of determination (R2), RF achieves the best result with a value of 0.610, followed by MLR with 0.462, and VHS with 0.313. These findings highlight the superior adaptability of the RF method in estimating bathymetry across varying depth zones using optical satellite imagery.
Analysis of Flood Vulnerability and Rainfall Changes in the Angke-Pesanggrahan Watershed using Spatial Mapping Fitria, Ratu Kenanga; Ruhiat, Yayat; Oktarisa, Yuvita
JURNAL GEOCELEBES Vol. 10 No. 1: April 2026
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v10i1.48347

Abstract

This study analyzes flood vulnerability in the Angke-Pesanggrahan Watershed, Jakarta, which faces increased risks due to land-use changes. The study aims to calculate the 50-year return period flood discharge, map flood-prone zones, and formulate mitigation recommendations using spatial mapping. A quantitative approach was employed, analyzing 15 years of rainfall data from five stations. Methodology included data consistency testing, Spearman’s correlation, stationarity, and outlier identification, followed by regional rainfall analysis using Thiessen Polygons. The Log Pearson Type III distribution was applied for frequency analysis, and the Nakayasu Synthetic Unit Hydrograph method estimated flood discharge. Flood-prone zones were mapped using scoring and overlay techniques in a Geographic Information System (GIS). Results show that the 50-year flood discharge reaches 1.128 m3/s, exceeding existing river capacity. Mapping simulations identified flood depths of 3–6 meters in downstream areas, with high-risk zones concentrated in Northern Kembangan, Kedaung Kali Angke, Kapuk Muara, Kamal Muara, Eastern Cengkareng, and Northern Kedoya, where surface runoff contributes up to 90%. Spatial analysis categorized 257.18 km2 as non-prone, 92.14 km2 as moderately prone, 75.75 km2 as prone, and 58.57 km2 as highly prone. This study concludes that the Angke-Pesanggrahan Watershed, particularly the Cengkareng Drain section, requires urgent technical intervention, including river normalization and catchment area optimization. These findings provide a crucial spatial database for sustainable flood mitigation and risk-based decision-making in urban planning.
Identification of Magma Intrusion Distribution in the Sekincau Mountain Area Based on the Euler Deconvolution Method of Gravity Data: Application of Gravity-Based Euler Deconvolution for Intrusive Mapping Amanda, Anisa; Agustian, Rizki Buana; Fista, Aksela Dian; Dani, Ilham
JURNAL GEOCELEBES Vol. 10 No. 1: April 2026
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v10i1.49005

Abstract

Mount Sekincau, West Lampung, is located within the active Bukit Barisan tectonic zone and exhibits geothermal potential controlled by magmatic activity and geological structures. This study aims to identify the distribution and depth of magmatic intrusions using gravity data analysis and Euler deconvolution. GGMPlus satellite gravity data were processed to generate Complete Bouguer Anomaly, regional and residual anomalies, analytical signal, Euler solutions, and three-dimensional models. The Complete Bouguer Anomaly values range from 38.05 to 58.32 mGal, with high anomalies concentrated in the central part of the study area. Positive residual anomalies ranging from 0.88 to 2.78 mGal indicate the presence of shallow high-density bodies interpreted as magmatic intrusions. Analytical signal and Euler deconvolution results with a structural index of 0 reveal clusters of shallow sources associated with fault zones. Three-dimensional modeling confirms a southeastward-oriented intrusive body. These results indicate that shallow magmatic intrusions act as the primary heat source of the Sekincau geothermal system.
Surface Ocean Current Variability Near Selayar Island During the Three El Niño-Southern Oscillation (ENSO) Phases Andika, Andika; Warouw, Gladiva
JURNAL GEOCELEBES Vol. 10 No. 1: April 2026
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v10i1.49626

Abstract

This study investigates the seasonal and interannual variability of surface ocean currents around Selayar Island, Indonesia, with a focus on differences among the three phases of the El Niño–Southern Oscillation (ENSO). Monthly surface current data from 1993 to 2020 were analyzed using climatological, composite, and anomaly approaches. The results reveal a spatially heterogeneous current structure that is dominated by seasonal variability, with domain-averaged current magnitudes ranging from approximately 0.085–0.305 ms-1. Interannual variability related to ENSO is evident mainly in the magnitude of surface current anomalies, which range approximately 0.03–0.05 ms-1 during El Niño and increase to about 0.07–0.09 ms-1 during La Niña, with peak values reaching ~0.10–0.12 ms-1. This indicates that ENSO primarily modulates current intensity rather than flow direction. Differences in anomaly direction are more pronounced under Neutral conditions, where anomaly patterns differ from those observed during both El Niño and La Niña phases. Overall, the results indicate that ENSO acts as an interannual modulation of surface currents, while monsoonal forcing remains the primary control on surface current dynamics in the study region.
Stratigraphy and Paleoenvironment of the Kuaro Formation, Muru River, Kutai Basin: A Paleontological Approach Prabowo, Iwan; Pratikno, Fathony Akbar; Putri, Efrina Chandra Agusti; Jamaluddin, Jamaluddin; Andrean, Eliza Putri; Kaunang, Imanuel
JURNAL GEOCELEBES Vol. 10 No. 1: April 2026
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v10i1.47264

Abstract

The southern margin of the Kutai Basin remains poorly constrained regarding its Paleogene history compared to the well-studied northern depocenter. This research investigates the stratigraphic characteristics, relative ages, and depositional environments of the Kuaro Formation along the Muru River, Paser Regency. The study integrates a detailed measuring section with biostratigraphic analyses of Larger Benthic Foraminifera (LBF), calcareous nannofossils, and palynology to reconstruct the paleoenvironmental evolution. The results reveal a continuous stratigraphic succession spanning from the Late Eocene to the Late Oligocene. The lower interval comprises coal-bearing siliciclastics deposited in a coastal swamp environment, marking the initial terrestrial influence. This unit transitions upward into massive Pellatispira and Discocyclina-bearing rudstones, indicating the development of a stable shallow-marine carbonate platform during the Late Eocene. The sequence culminates in Late Oligocene fine-grained calcareous claystones yielding Reticulofenestra bisecta and Reticulofenestra lockeri, deposited in a lower-energy inner shelf setting. This vertical stacking pattern records a major transgressive phase, evolving from terrestrial-influenced environments to open marine conditions. These findings provide significant insights into the Eocene–Oligocene transition in the southern Kutai Basin, distinguishing its retrogradational stratigraphic architecture from the progradational deltaic cycles typical of the younger Neogene sequences in the northern basin.

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