Analysis of Earthquake Potential along the Coastal Region of South Java using Semi-Markov Models as a Tsunami Mitigation

Athaya Rahma  Puteri; Halimatus Sa'diyah; Alfia Nur Fauziah; Christina Agustin Raphonhita Simbolon; Ramadhani Latief Firmansyah; Dwi Ertiningsih

doi:10.22342/jims.v32i1.1556

Athaya Rahma Puteri ⁽¹⁾ , Halimatus Sa'diyah ⁽²⁾ , Alfia Nur Fauziah ⁽³⁾ , Christina Agustin Raphonhita Simbolon ⁽⁴⁾ , Ramadhani Latief Firmansyah ⁽⁵⁾ , Dwi Ertiningsih ⁽⁶⁾

(1) Department of Mathematics, Universitas Gadjah Mada, Indonesia, Indonesia,

(2) Department of Mathematics, Universitas Gadjah Mada, Indonesia, Indonesia,

(3) Department of Mathematics, Universitas Gadjah Mada, Indonesia, Indonesia,

(4) Department of Mathematics, Universitas Gadjah Mada, Indonesia, Indonesia,

(5) Department of Mathematics, Universitas Gadjah Mada, Indonesia, Indonesia,

(6) Department of Mathematics, Universitas Gadjah Mada, Indonesia, Indonesia

https://doi.org/10.22342/jims.v32i1.1556

Issue
Vol. 32 No. 1 (2026): MARCH

Submitted
October 25, 2023

Accepted
February 17, 2025

Published
January 5, 2026

Keywords:

semi-Markov model, earthquake forecasting, tsunami, south coast of Java, Mean Absolute Percentage Error (MAPE)

PDF

Abstract

This study applies a semi-Markov model to assess earthquake occurrence in the South Java coastal region. The main objective is to forecast earthquakes in this area, considering three key factors: geographic location, timing, and seismic magnitude. The South Java coastal region is chosen for this study due to its proximity to the island of Java, the economic hub of Indonesia. The study divides the South Java coastal region into five distinct zones and categorizes earthquakes into three magnitude groups. The results predict that earthquakes will occur in the South Coast regions of East Java, Central Java, or West Java between December 26, 2022, and November 20, 2023. Additionally, projections suggest that earthquakes are likely to occur in East Java, West Java, or Banten between November 21, 2023, and December 31, 2030. The estimated magnitudes range from 5 to 6 Mw. The findings also indicate that no tsunamis are expected along the South Java coast until 2030. Model validation using the Mean Absolute Percentage Error (MAPE) results in a value of 4.224\%. This confirms the high accuracy of the predictions. Although no tsunamis are forecasted, the public must remain alert and prepared for the anticipated earthquakes. These findings provide important insights for disaster mitigation and emphasize the need for ongoing monitoring, early warning systems, and community preparedness to minimize potential risks

Full text article

Generated from XML file

References

C. W. Churchman, R. L. Ackoff, and E. L. Arnoff, “Introduction to operations research.,” 1957. https://doi.org/10.2307/2227681.

N. Meade, “Industrial and business forecasting methods, lewis, cd, borough green, sevenoaks, kent: Butterworth, 1982. price:£ 9.25. pages: 144,” 1983. https://doi.org/10.1002/FOR.3980020210.

M. A. Jafari, “Statistical prediction of the next great earthquake around Tehran, Iran,” Journal of Geodynamics, vol. 49, no. 1, pp. 14–18, 2010. https://dx.doi.org/10.1016/j.jog.2009.07.002.

D. Vere-Jones, “Forecasting earthquakes and earthquake risk,” International Journal of Forecasting, vol. 11, no. 4, pp. 503–538, 1995. https://doi.org/10.1016/0169-2070(95)00621-4.

D. S. Harte, “Log-likelihood of earthquake models: evaluation of models and forecasts,” Geophysical Journal International, vol. 201, no. 2, pp. 711–723, 2015. https://doi.org/10.1093/gji/ggu442.

C. Gkarlaouni, E. Papadimitriou, S. Lasocki, G. Lizurek, V. Karakostas, and A. Kilias, “Stochastic analysis of earthquake activity in two seismogenic fault systems in greece.,” Bulletin of the Geological Society of Greece, vol. 47, no. 3, pp. 1099–1108, 2013. https://doi.org/10.12681/bgsg.10965.

R. Sadeghian, “The effects of zoning methods on forecasting of the next earthquake occurrences, according to semi-Markov models,” Annals of Geophysics, vol. 53, no. 5-6, pp. 83–97, 2010. https://pdfs.semanticscholar.org/bbe6/fbe66c0f51b9daa74235a397e6da0aef8f33.pdf.

A. S. N. Alarifi, N. S. N. Alarifi, and S. Al-Humidan, “Earthquakes magnitude predication using artificial neural network in northern red sea area,” Journal of King Saud University-Science, vol. 24, no. 4, pp. 301–313, 2012. https://doi.org/10.1016/j.jksus.2011.05.002.

R. Sadeghian, “Forecasting time and place of earthquakes using a semi-Markov model (with case study in Tehran province),” Journal of Industrial Engineering International, vol. 8, no. 1, p. 20, 2012. https://link.springer.com/article/10.1186/2251-712X-8-20.

P. C. M. de Bruin, “Semi-markov model applied to the estimation of earthquake occurrences,” B.S. thesis, 2019. https://studenttheses.uu.nl/bitstream/handle/20.500.12932/32997/Thesis%20(Patricia%20de%20Bruin).pdf.

S. Kim and H. Kim, “A new metric of absolute percentage error for intermittent demand forecasts,” International Journal of Forecasting, vol. 32, no. 3, pp. 669–679, 2016. https://doi.org/10.1016/j.ijforecast.2015.12.003.

S. Widiyantoro, E. Gunawan, A. Muhari, N. Rawlinson, J. Mori, N. R. Hanifa, S. Susilo, P. Supendi, H. A. Shiddiqi, A. D. Nugraha, et al., “Implications for megathrust earthquakes and tsunamis from seismic gaps south of java indonesia,” Scientific reports, vol. 10, no. 1, p. 15274, 2020. https://www.nature.com/articles/s41598-020-72142-z.