Neural Network for Earthquake Prediction Based on Automatic Clustering in Indonesia

Mohammad Nur Shodiq, Dedy Hidayat Kusuma, Mirza Ghulam Rifqi, Ali Ridho Barakbah, Tri Harsono


A model of artificial neural networks (ANNs) is presented in this paper to predict aftershock during the next five days after an earthquake occurrence in selected cluster of Indonesia with magnitude equal or larger than given threshold. The data were obtained from Indonesian Agency for Meteorological, Climatological and Geophysics (BMKG) and United States Geological Survey’s (USGS). Six clusters was an optimal number of cluster base-on cluster analysis implementing Valley Tracing and Hill Climbing algorithm, while Hierarchical K-means was applied for datasets clustering. A quality evaluation was then conducted to measure the proposed model performance for two different thresholds. The experimental result shows that the model gave better performance for predicting an aftershock occurrence that equal or larger than 6 Richter’s scale magnitude.


Artificial neural networks; earthquake prediction; cluster analysis

Full Text:



Georgoulas, G., A. Konstantaras, E. Katsifarakis, C.D. Stylios, E. Maravelakis, and G.J.Vachtsevanos. Seismic-mass Density-based Algorithm for Spatio-temporal Clustering. Expert Systems with Applications. 2013; 40(10): 4183-4189

Alvarez, R. J., J. C. Echeverria, A. Ortiz-Cruz, and E. Hernandez. Temporal and Spatial Variations of Seismicity Scaling Behavior in Southern México. Journal of Geodynamics. 2012; 54:1-12.

Ales, S., and Jirí Vanek. Earthquake Clustering in the Tectonic Pattern and Volcanism of the Andaman Sea Region. Tectonophysics. 2013; 608: 728-736.

C.R. Allen, Responsibilities in Earthquake Prediction. Bulletin of the Seismological Society of America. 1982; 66(6): 2069–2074.

E.I. Alves. Earthquake Forecasting using Neural Networks: Results Future Work. Nonlinear Dynamics. 2006; 44(1–4): 341–349.

H. Adelli and K. Panakkat. A Probabilistic Neural Network for Earthquake Magnitude Prediction. Neural Network. 2009; 22(7): 1018-1024.

J. Reyes, A. Morales-Esteban, and F. Martínez-Álvarez. Neural Networks to Predict Earthquakes in Chile. Applied Soft Computing. 2013; 13(2): 1314–1328.

A. Morales-Esteban, F. Martínez-Álvarez, S. Scitovski, R. Scitovski. A Fast Partitioning Algorithm using Adaptive Mahalanobis Clustering with Application to Seismic Zoning. Computers & Geosciences. 2014; 73: 132-141.

A.R. Barakbah and K. Arai. Determining Constraints of Moving Variance to Find Global Optimum and Make Automatic Clustering. Industrial Electronics Seminar (IES). Surabaya. 2004: 409-413.

A.R. Barakbah and K. Arai. Reserved Pattern of Moving Variance for Accelerating Automatic Clustering. EEPIS Journal. 2004; 2(9): 15-21.

M.N. Shodiq, A. R. Barakbah, T. Harsono. Spatial Analysis of Earthquake Distribution with Automatic Clustering for Prediction of Earthquake Seismicity in Indonesia. The Fourth Indonesian-Japanese Conference on Knowledge Creation and Intelligent Computing (KCIC). Surabaya/Bali. 2015: 47-55.

D.A. Yuen, J.K. Benamin, F. B. Evan, W. Dzwinel, A.G. Zachary, and R.S. Cesar. Clustering and Visualization of Earthquake Data in a Grid Environment. Visual Geoscience. 2005; 10(1): 1-12

K. Arai and A.R. Barakbah. Hierarchical K-means: an Algorithm for Centroids Initialization for K-means. Reports of the Faculty of Science and Engineering, Saga University, Japan. 2007: 36(1).

A. Zamani and R.M. Sorbi. Application of Neural Network and ANFIS Model for Earthquake Occurrence in Iran. Earth Science Informatics. 2013; 6(2): 71-85.

A. Morales-Esteban, F. Martínez-Álvarez, J. Reyes. Earthquake prediction in seismogenic areas of the Iberian Peninsula based on computational intelligence. Tectonophysics. 2013; 593: 121–134

M.N. Shodiq, A.R. Barakbah, T. Harsono. Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquake in Indonesia. International Journal of Engineering Technology (EMITTER). 2015; 3(1): 53-67.



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

JOIV : International Journal on Informatics Visualization
Published by Information Technology Department
Politeknik Negeri Padang, Indonesia

© JOIV - ISSN : 2549-9610 | e-ISSN : 2549-9904 

Phone : +62-82386434344
Email  :

Creative Commons License is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

View My Stats