Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

  • Mohammad Nur Shodiq Electronic Engineering Polytechnic Institute of Surabaya
  • Ali Ridho Barakbah Electronic Engineering Polytechnic Institute of Surabaya
  • Tri Harsono Electronic Engineering Polytechnic Institute of Surabaya


Spatio temporal data clustering is challenge task. The result of clustering data are utilized to investigate the seismic parameters. Seismic parameters are used to describe the characteristics of earthquake behavior. One of the effective technique to study multidimensional spatio temporal data is visualization. But, visualization of multidimensional data is complicated problem. Because, this analysis consists of observed data cluster and seismic parameters. In this paper, we propose a visualization system, called as IES (Indonesia Earthquake System), for cluster analysis, spatio temporal analysis, and visualize the multidimensional data of seismic parameters. We analyze the cluster analysis by using automatic clustering, that consists of get optimal number of cluster and Hierarchical K-means clustering. We explore the visual cluster and multidimensional data in low dimensional space visualization. We made experiment with observed data, that consists of seismic data around Indonesian archipelago during 2004 to 2014.

Keywords: Clustering, visualization, multidimensional data, seismic parameters.


Download data is not yet available.


BMKG Sanglah Denpasar, Geodinamika Informasi Meteorologi Klimatologi dan Geofisika, BMKG Sanglah Denpasar, Vol.2, No.11, 2013.

______________ , Analisis Potensi Rawan Bencana Alam di Papua dan Maluku (Tanah Longsor – Banjir – Gempa Bumi - Tsunami), Laporan Akhir, Deputi Bidang Pembinaan Sarana Teknis dan Peningkatan Kapasitas, Kementerian Negara Lingkungan Hidup, Jakarta, 2007.

Irsyam, Masyhur. Dkk., Ringkasan Hasil Studi Tim Revisi Peta Gempa Indonesia 2010, Tim Revisi Peta Gempa Indonesia, Bandung, 2010.

Dzwinel, W. Yuen, D. Kaneko, Y. Boryczko, K. Ben-Zion, K., Multi-resolution clustering analysis and 3-D visualization of multitudinous synthetic earthquakes, Vis Geosci, Vol. 8, pp. 12–25, 2003.

Mohammad Nur Shodiq, Ali Ridho Barakbah, Tri 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) 2015, Surabaya/Bali, Indonesia, March 24-26, 2014.

Yuen, Dave A., Benamin J.K., Evan F.B., Dzwinel W., Zachary A.G., Cesar R.S., Clustering and visualization of earthquake data in a grid environment, Visual GeoScience, 2005.

Yuen, D.A. Benjamin, J.K. Bollig, E.F. Dzwinel, W. Garbow, Z.A. Silva, Clustering and visualization of earthquake data in a grid environment, Vis Geosci, Vol. 10, pp. 1–12, 2006.

Yuen, D.A., Dzwinel, W., Ben-Zion, Y., Kadlecd, B., Visualization of Earthquake Clusters over Multidimensional Space, Encyclopedia of Complexity and Systems Science, pp 2347-2371, 2009.

Dzwinel, Witold dkk., Cluster Analysis, Data-Mining, Multi-dimensial Visualization of Earthquakes Over Spase, Time and Feature Spase, Earth and Planetary Sci. Letter, 2003.

Rohadi, Supriyanto, Studi Seismotektonik Sebagai Indikator Potensi Gempa bumi di Wilayah Indonesia, Jurnal Meteorologi dan Geofisika, Vol. 10, No. 2, pp. 111–120, 2009.

Sunardi, Bambang, Analisa Fraktal dan Rasio Slip Daerah Bali-NTB Berdasarkan Pemetaan Variasi Parameter Tektonik, Jurnal Meteorologi dan Geofisika, Vol. 10, No.1, 2009.

Ali Ridho Barakbah, Kohei Arai, Centronit: Initial Centroid Designation Algorithm for K-Means Clustering, EMITTER International Journal of Engineering Technology, Vol. 02, No. 01, 2014.

Ali Ridho Barakbah, Kohei Arai, Determining constraints of moving variance to find global optimum and make automatic clustering, Proc. Industrial Electronics Seminar (IES) 2004, Surabaya, Indonesia, pp. 409-413, October 12, 2004.

Kohei Arai, Ali Ridho Barakbah, Hierarchical K-means: an algorithm for centroids initialization for K-means, Reports of the Faculty of Science and Engineering, Saga University, Japan, Vol. 36, No. 1, 2007.

Zamani, ahmad. Sorbi, Reza M., Application of neurol network and ANFIS model for earthquake occurrance in Iran, Earth Sci Inform, DOI:10.1007/s12145-013-0112-8, Spinger-Verlag Berlin Heidelberg, 2003.

N. Andrienko, G. Andrienko, P. Gatalsky, Exploratory spatio-temporal visualization: an analytical review, Journal of Visual Languages and Computing, Vol. 14, pp. 503–541, 2003.

E. Florido, F. Martínez-Ãlvarez, A. Morales-Esteban, J. Reyes, J.L. Aznarte-Mellado, Detecting precursory patterns to enhance earthquake prediction in Chile, Computers and Geosciences,, 2014.

Rohadi, Supriyanto, dkk., Studi Variasi Spatial Seismisitas Zona Subduksi Jawa, Jurnal Meteorologi Dan Geofisika, Vol 8, No.1, Juli, 2007

Grijalva, S., Multi-Dimensional, Multi-Scale Modeling and Algorithms for Integrating Variable Energy Resources in Power Networks: Challenges and Opportunities, Published by Elsevier Inc., 2014.

Buja, A. Cook, D. Swayne, D.F., Interactive high dimensional data visualization, Journal of Computational and Graphical Statistics, Vol. 5, No. 1, pp. 78-99, 1996.

Oosterom, Peter van. Stoter, J., 5D Data Modelling: Full Integration of 2D/3D Space, Time, and Scale Dimension, GIScience, LNCS 6292, pp. 310-324, 2010.

Jamileh Vasheghani Farahani, J. V., Monitoring the Variations of b-Value and Seismicity in the Makran Ranges, the Absence of a Notable Event in West of Makran Subduction Zone, Geodynamics Research International Bulletin (GRIB), Vol. 2, No. 02, SN:06, Summer, 2014.

Rohadi, S., Studi Seismotektonik Sebagai Indikator Potensi Gempa Bumi di Wilayah Indonesia. Balai Besar Meteorologi dan Geofisika Wilayah II Jakarta, 2009.

How to Cite
Shodiq, M. N., Barakbah, A. R., & Harsono, T. (2016). Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia. EMITTER International Journal of Engineering Technology, 3(1), 53-67.