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INDONESIA
Jurnal Meteorologi dan Geofisika
Published by Pusat Penelitian dan Pengembangan, Badan Meteorologi Klimatologi dan Geofisika
ISSN : 14113082     EISSN : 25275372     DOI : https://doi.org/10.31172/jmg
Core Subject : Science,
Earth & Planetary Sciences Energy Physics
Jurnal Meteorologi dan Geofisika (JMG) is a scientific research journal published by the Research and Development Center of the Meteorology, Climatology, and Geophysics Agency (BMKG) as a means to publish research and development achievements in Meteorology, Climatology, Air Quality and Geophysics.
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Ilmu Bumi dan Planet (Lain-Lain)
Articles 4 Documents
 1 
Search results for , issue "Vol. 26 No. 2 (2025)" : 4 Documents clear
Tsunami Evacuation Route Mapping in the Tegalkamulyan Area, Cilacap Regency, Based on the Potential of a South Java Earthquake Saputri, Aliffia Retno Maya; Muqoddas, Muhamad Mahfud; Irayani, Zaroh
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.v26i2.917

Abstract

Cilacap Regency is one of Indonesia’s rapidly developing regions, particularly in the oil mining industry, but it is also highly vulnerable to tsunami hazards due to its location along the South Java subduction zone. A major tsunami generated by a large earthquake in this zone would severely impact coastal areas, including the Tegalkamulyan area. As part of disaster mitigation efforts, this study conducted tsunami evacuation route mapping using tsunami wave propagation modeling based on the Shallow Water Equations (SWE). The simulations employed three hypothetical South Java earthquake sources proposed by the National Earthquake Study Center in 2017, with magnitudes up to Mw 8.7. Among these, Scenario 5 represents the worst-case scenario, producing the largest vertical displacement, with a wave uplift of 11.418 m and a subsidence of −7.476 m. The results show that tsunami waves propagate in all directions, with the fastest arrival time reaching the coast 44 minutes and 1 second after the earthquake. The maximum inundation distance extends up to 12.7 km from the coastline, covering an area of 534.890 km², with a maximum run-up height of 30.847 m. Based on the evacuation route mapping, vertical evacuation directs residents to seek tall buildings or Temporary Evacuation Sites within approximately 6–23 minutes on foot, while horizontal evacuation routes guide evacuees from Temporary Evacuation Sites to Final Evacuation Sites within approximately 13–20 minutes using motorized vehicles at an average speed of 38 km/h.
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.
Leveraging Sequential and Attention-Based Deep Learning Architectures for Accurate Daily Rainfall Prediction in Jakarta, Indonesia, Using Atmospheric Predictors Hardiano, Akhdan Fadhilah Yaskur; Setiawan, Sonni
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.v26i2.1194

Abstract

In this study, we developed and evaluated daily rainfall prediction models utilizing deep learning architectures, specifically comparing Long Short-Term Memory (LSTM) and Transformer models integrated with various atmospheric predictors. Our results indicate that the LSTM achieved superior accuracy at short-term lags—reaching an R² of 0.94 and an RMSE as low as 4.81 at lag-3—whereas the Transformer demonstrated higher consistency across all lags, maintaining stable R² values between 0.87 and 0.88. The application of a 5-day smoothing pre-processing step significantly enhanced prediction quality for both architectures by mitigating high-frequency noise, a benefit particularly pronounced in the LSTM due to its sensitivity to data fluctuations. Notably, the inclusion of tropical wave variables did not substantially improve model performance and, in some instances, reduced LSTM accuracy at longer lags by increasing input complexity; conversely, the Transformer remained robust to these additional variables. Among the predictors evaluated, Vertically Integrated Moisture Flux Divergence (VIMD) emerged as the most critical feature, underscoring its physical relevance to precipitation processes in convective and monsoonal regions. These findings suggest that while LSTMs excel at capturing immediate temporal dynamics, Transformers provide a more stable framework for longer-range rainfall forecasting in Jakarta.
Network-Based Equity Evaluation of Tsunami Evacuation Access for a Megathrust Scenario in Palabuhanratu: English Sudibyo, Reno; Kurniadi, Anwar; Subiyanto, Adi; Ramadhan, Fajar Gilang
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.v26i2.1196

Abstract

We present a network-based equity evaluation of tsunami evacuation access for a megathrust scenario in Palabuhanratu, quantifying both individual safety attainment and the spatial distribution of access. By overlaying physics-based inundation data with a road graph, we compute multimodal time-to-safety and isochrones, summarizing village-level access through overall reachability (RR), Gini, and hazard-weighted Gini (Gini*) indices. Evacuation time allowances (ETAs) are set at 22, 18, and 15 minutes—validated against site-specific arrival modeling and real-world departure observations from the 2024 Noto event—revealing a critical temporal tipping point. While an ETA of 22 minutes ensures total reachability (RR=1.00) with low inequality, tightening the window to 18 and 15 minutes sharply reduces RR and increases Gini* scores. Furthermore, the addition of an alternative Tsunami Evacuation Area (TEA) at Smile Hill yields localized time savings and minor gains in specific clusters at 22 minutes, yet provides no systemwide benefit at shorter ETAs, indicating that time scarcity dominates access during tight windows. Methodologically, this study employs "beat-the-wave" logic and least-cost routing on OSMnx/NetworkX graphs, offering a reproducible screening tool that integrates access, fairness, and hazard emphasis for TEA design under time-critical evacuation constraints.

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