Journal of Multidisciplinary Applied Natural Science
##plugins.themes.gdThemes.journalSlogan##
Scopus CiteScore 2024
4.8
Calculated on 05 May, 2025
SJR 2024
0.31
Powered by scimagojr.com
##plugins.themes.gdThemes.journalSlogan##
4.8
Calculated on 05 May, 2025
0.31
Powered by scimagojr.com
https://doi.org/10.47352/jmans.2774-3047.312
Triyana Muliawati
Fuji Lestari
Danni Gathot Harbowo
Sumatra Island is located in the Pacific Ring of Fire, which has resulted in high seismic activity. Several large earthquakes have been recorded in this region. Earthquake hazards lead to loss of life, damage to building infrastructure, losses in production sectors, and cross-sectoral losses. Hazard mitigation is necessary by calculating earthquake insurance premiums to anticipate disaster risks in earthquake-prone areas. This study aims to estimate the value of earthquake insurance premiums in Lampung Province based on the probability of an earthquake occurring at an intensity (SHI), defined as seismic hazard intensity, derived from the peak ground acceleration (PGA) and damage ratio calculations. We compiled multivariate data that can reveal periodic earthquake activity patterns, such as detailed information on earthquake activity over the past three decades and building damage data. The analysis results show that the larger the PGA value, the smaller the SHI value. The average damage ratio for all buildings indicates that the more significant the proportion of severe damage, the higher the average building damage ratio. Residential buildings have the highest estimated pure premium due to the use of simple materials that are highly vulnerable to earthquakes. Understanding these statistical patterns is crucial for comprehensively assessing earthquake disaster threats in the long term. The goal is to enable more effective disaster risk mitigation for frequent earthquake activity in the Lampung Province in the future.
[1] F. N. Ani, D. G. Harbowo, T. Muliawati, T. Kazuhiro, and A. Setyawan. (2024). "State transition matrix and Markov-chain diagram for frequent volcanic eruptions: Krakatoa, Indonesia". E3S Web of Conferences. 479. 10.1051/e3sconf/202447902005.
DOI: https://doi.org/10.1051/e3sconf/202447902005[2] D. G. Harbowo, T. Muliawati, and P. A. Rahmi. (2024). "Analisis Pola Aktivitas Gempa Bumi di Pulau Sumatera dengan Metode K-Means Clustering dan Rantai Markov". Prosiding Seminar Nasional Sains Data. 4 (1): 592-601. 10.33005/senada.v4i1.291.
DOI: https://doi.org/10.33005/senada.v4i1.291[3] D. G. Harbowo, T. Muliawati, and G. A. Rifa'i. (2024). "Analisis Probabilitas Gempa Bumi di Pulau Jawa Menggunakan Model Markov Chain". Prosiding Seminar Nasional Sains Data. 4 (1): 602-614. 10.33005/senada.v4i1.292.
DOI: https://doi.org/10.33005/senada.v4i1.292[4] D. G. Harbowo. (2023). "An Assessment of The Scientific Value of Krakatoa, Indonesia From a Geoheritage Perspective". Journal of Applied Geoscience and Engineering. 2 (1): 11-25. 10.34312/jage.v2i1.19360.
[5] T. Muliawati and D. G. Harbowo. (2023). "A Statistical review of the dates and patterns of volcanic activity of Lewotolo Volcano, East Nusa Tenggara, Indonesia". IOP Conference Series: Earth and Environmental Science. 1245 (1): 10.1088/1755-1315/1245/1/012006.
DOI: https://doi.org/10.1088/1755-1315/1245/1/012006[6] F. Brigitta, F. Lestari, and K. F. Afifah. (2024). "Estimation of Earthquake Insurance Premium by Considering Earthquake Probability and the Damage Ratio of Buildings in Banda Aceh and Sibolga City". Journal of Science and Applicative Technology. 8 (1). 10.35472/jsat.v8i1.1719.
DOI: https://doi.org/10.35472/jsat.v8i1.1719[7] A. King, D. Middleton, C. Brown, D. Johnston, and S. Johal. (2014). "Insurance: Its Role in Recovery from the 2010–2011 Canterbury Earthquake Sequence". Earthquake Spectra. 30 (1): 475-491. 10.1193/022813eqs058m.
DOI: https://doi.org/10.1193/022813EQS058M[8] N. Radu and F. Alexandru. (2022). "Parametric Insurance—A Possible and Necessary Solution to Insure the Earthquake Risk of Romania". Risks. 10 (3). 10.3390/risks10030059.
DOI: https://doi.org/10.3390/risks10030059[9] J. Pai, Y. Li, A. Yang, and C. Li. (2022). "Earthquake parametric insurance with Bayesian spatial quantile regression". Insurance: Mathematics and Economics. 106 : 1-12. 10.1016/j.insmatheco.2022.04.007.
DOI: https://doi.org/10.1016/j.insmatheco.2022.04.007[10] R. Mumo and R. Watt. (2019). "Residential insurance market responses after earthquake: A survey of Christchurch dwellers". International Journal of Disaster Risk Reduction. 40. 10.1016/j.ijdrr.2019.101166.
DOI: https://doi.org/10.1016/j.ijdrr.2019.101166[11] J. H. Lin. (2018). "Earthquake insurance pricing: a risk-based approach". Disasters. 42 (2): 392-404. 10.1111/disa.12247.
DOI: https://doi.org/10.1111/disa.12247[12] J. M. Liu, T. Wang, S. R. Wu, and M. T. Gao. (2016). "New Empirical Relationships between Arias Intensity and Peak Ground Acceleration". Bulletin of the Seismological Society of America. 106 (5): 2168-2176. 10.1785/0120150366.
DOI: https://doi.org/10.1785/0120150366[13] T. Zera, A. R. Fauziah, M. Nafian, and A. Ramadhani. (2022). "Mapping of Peak Ground Acceleration (PGA) Values using the Donovan Model for Sumatran". Journal of Physics: Conference Series. 2243 (1). 10.1088/1742-6596/2243/1/012031.
DOI: https://doi.org/10.1088/1742-6596/2243/1/012031[14] D. J. Wald, V. Quitoriano, T. H. Heaton, and H. Kanamori. (1999). "Relationships between Peak Ground Acceleration, Peak Ground Velocity, and Modified Mercalli Intensity in California". Earthquake Spectra. 15 (3): 557-564. 10.1193/1.1586058.
DOI: https://doi.org/10.1193/1.1586058[15] A. Anugrayanti, M. Arsyad, and V. A. Tiwow. (2021). "Analysis of susceptible disaster region based on the peak ground acceleration and earthquake intensity in Mamasa 2018". Journal of Physics: Conference Series. 1816 (1). 10.1088/1742-6596/1816/1/012014.
DOI: https://doi.org/10.1088/1742-6596/1816/1/012014[16] J. M. Liu, M. T. Gao, and J. J. Xie. (2015). "Spatial Variability and Attenuation of Arias Intensity during the 1999 Chi‐ChiMw 7.6 Earthquake, Taiwan". Bulletin of the Seismological Society of America. 105 (3): 1768-1778. 10.1785/0120140157.
DOI: https://doi.org/10.1785/0120140157[17] A. Masi, L. Chiauzzi, G. Nicodemo, and V. Manfredi. (2020). "Correlations between macroseismic intensity estimations and ground motion measures of seismic events". Bulletin of Earthquake Engineering. 18 (5): 1899-1932. 10.1007/s10518-019-00782-2.
DOI: https://doi.org/10.1007/s10518-019-00782-2[18] M. Ramdhan, P. Priyobudi, R. T. Imananta, M. Muzli, P. Supendi, Y. H. Perdana, J. Nugraha, J. Jatnika, Y. H. Ali, A. L. Panjaitan, M. F. Nugraha, S. Kristyawan, A. S. Sembiring, A. R. Setyahagi, and D. S. Yogaswara. (2019). "Katalog Gempabumi Signifikan dan Merusak 1821-2018". Badan Meteorologi Klimatologi dan Geofisika.
[19] P. N. Rahmaddi. (2021). "Buku Pedoman Survey Kerusakan Bangunan".
[20] C. Del Gaudio, G. De Martino, M. Di Ludovico, G. Manfredi, A. Prota, P. Ricci, and G. M. Verderame. (2016). "Empirical fragility curves from damage data on RC buildings after the 2009 L’Aquila earthquake". Bulletin of Earthquake Engineering. 15 (4): 1425-1450. 10.1007/s10518-016-0026-1.
DOI: https://doi.org/10.1007/s10518-016-0026-1[21] A. Deniz. (2006) . "Estimation of earthquake insurance premium rates based stochastic methods". Middle East Technical University.
[22] V. M. Zobin, J. F. Ventura-Ramírez, C. L. Gutiérrez-Andrade, L. H. Cruz, and S. Santibáñez-Ibáñez. (2006). "The Mw 7.4 Colima, Mexico, Earthquake of 21 January 2003: The Observed Damage Matrix in Colima City and its Comparison with the Damage Probability Matrix". Natural Hazards. 38 (3): 391-410. 10.1007/s11069-005-2074-8.
DOI: https://doi.org/10.1007/s11069-005-2074-8[23] K. Jaiswal, D. Wald, and D. D'Ayala. (2011). "Developing Empirical Collapse Fragility Functions for Global Building Types". Earthquake Spectra. 27 (3): 775-795. 10.1193/1.3606398.
DOI: https://doi.org/10.1193/1.3606398[24] S. Lagomarsino and S. Giovinazzi. (2006). "Macroseismic and mechanical models for the vulnerability and damage assessment of current buildings". Bulletin of Earthquake Engineering. 4 (4): 415-443. 10.1007/s10518-006-9024-z.
DOI: https://doi.org/10.1007/s10518-006-9024-z[25] S. A. Klugman, H. H. Panjer, and G. E. Willmot. (2013). "Loss Models". 10.1002/9781118787106.
DOI: https://doi.org/10.1002/9781118787106[26] J. C. Montalvo‐Arrieta, R. L. Sosa‐Ramírez, and E. G. Paz‐Martínez. (2015). "Relationship between MMI Data and Ground Shaking in the State of Nuevo León, Northeastern Mexico". Seismological Research Letters. 86 (5): 1489-1495. 10.1785/0220140206.
DOI: https://doi.org/10.1785/0220140206[27] S. E. Hough. (2014). "Earthquake intensity distributions: a new view". Bulletin of Earthquake Engineering. 12 (1): 135-155. 10.1007/s10518-013-9573-x.
DOI: https://doi.org/10.1007/s10518-013-9573-x[28] S. Aribowo, D. Muslim, D. H. Natawidjaja, and M. R. Daryono. (2017). "Sub-Segmentasi Sesar Pada Segmen Kumering Antara Danau Ranau Hingga Lembah Suoh, Lampung Barat Subdivision Of Segmentation In Kumering Segment Between Ranau Lake To Suoh Valley, West Lampung". Jurnal Lingkungan Dan Bencana Geologi. 8 (1): 31-46.
[29] W. Triyoso and A. Suwondo. (2022). "From the geodynamic aspect to earthquake potential hazard analysis of Liwa city and its surrounding". Natural Hazards. 116 (1): 1329-1344. 10.1007/s11069-022-05705-0.
DOI: https://doi.org/10.1007/s11069-022-05705-0[30] D. S. Widarto, T. Yudistira, J.-I. Nishida, I. Katsura, E. Z. Gaffar, and S. Nishimura. (2016). "Imaging Rock Density Distribution beneath Liwa Fracture Zone in the Southern Part of the Great Sumatran Fault System, Indonesia". International Journal of Geosciences. 07 (04): 598-614. 10.4236/ijg.2016.74046.
DOI: https://doi.org/10.4236/ijg.2016.74046[31] A. Soehaimi, D. Muslim, I. Kamawan, and R. S. Negara. (2015). In: "Engineering Geology for Society and Territory - Volume 5, ch. Chapter 194". 1015-1019. 10.1007/978-3-319-09048-1_194.
DOI: https://doi.org/10.1007/978-3-319-09048-1_194[32] I. D. Gupta. (2002). "The State of the Art in Seismic Hazard Analysis". ISET Journal of Earthquake Technology. 10.63898/wnkz4526.
DOI: https://doi.org/10.63898/WNKZ4526