Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Muhammad Sukma, Rifaz
Unknown Affiliation
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Advanced Earthquake Magnitude Prediction Using Regression and Convolutional Recurrent Neural Networks Id Hadiana, Asep; Muhammad Sukma, Rifaz; Krishna Putra, Eddie
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5922

Abstract

Earthquake magnitude prediction is critical in seismology, with significant implications for disaster risk management and mitigation. This study presents a novel earthquake magnitude prediction model by integrating regression analysis with Convolutional Recurrent Neural Networks (CRNNs). It utilises Convolutional Neural Networks (CNNs) for spatial feature extraction from 2-dimensional seismic signal images and Long Short-Term Memory (LSTM) networks to capture temporal dependencies. The innovative model architecture incorporates residual connections and specialised regression techniques for sequential data. Validated against a comprehensive seismic dataset, the model achieves a Mean Squared Error (MSE) of 0.1909 and a Root Mean Squared Error (RMSE) of 0.4369, with a coefficient of determination of 0.79772. These metrics, alongside a correlation coefficient of 0.8980, demonstrate the model's accuracy and consistency in predicting earthquake magnitudes, establishing its potential for enhancing seismic risk assessment and informing early warning systems.
Co-Authors Hadiana, Asep Id Krishna Putra, Eddie