Terrorism vulnerability assessment in Java Island: a spatial multi-criteria analysis approach

https://doi.org/10.22146/ijg.45691

Asep Adang Supriyadi(1*), Masita Dwi Mandini Manessa(2)

(1) 1.Department of Defense Industry, Indonesia Defense University, Sentul, Indonesia and 2.National Counter Terrorism Agency, Sentul, Indonesia
(2) Department of Geography, University of Indonesia, Depok, Indonesia
(*) Corresponding Author

Abstract


Terrorism is one of the Indonesia’s national security threat. The attack mostly happens in Java Island, attracted by the dense population, also because the island is a center for economic and governance. The spatial pattern of terrorism attack shows correlations with the spatial density of the targeted attack. Therefore, this study assesses the spatial vulnerability of Java Island using a spatial multi-criteria analysis (SMCA). The main attributes analyzed were the density of the past terrorist attack, arrested area, police/military facility, government facility, business center, densely populated area, and church, determine that in the case of a terrorist attack is strongly affected by the attraction of the area.

 


Keywords


Terrorism; Vulnerability Index; Java Island; Spatial Multi-Criteria Decision

Full Text:

PDF


References

Acharya, A. (2006). The Bali Bombings: Impact on Indonesia and Southeast Asia. Center for Eurasian Policy Occasional Research Paper Series II (Islamism in Southeast Asia), 2, 1–5. Retrieved from https://www.hudson.org/content/researchattachments/attachment/517/acharyathebalibombings.pdf

Alius, S. (2018). Threats and Challenges of the Spread of the Radical Terrorism (Ancaman dan Tantangan Penyebaran Paham Radikal Terorisme). Jakarta.

Armaş, I., & Gavris, A. (2013). Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) – a case study for Bucharest, Romania. Natural Hazards and Earth System Sciences, 13, 1481–1499. https://doi.org/10.5194/nhess-13-1481-2013

Arva, B. J., & Piazza, J. A. (2016). Spatial Distribution of Minority Communities and Terrorism: Domestic Concentration versus Transnational Dispersion. Defence and Peace Economics, 27(1), 1–36. https://doi.org/10.1080/10242694.2015.1055091

Banica, A., Rosu, L., Muntele, I., & Grozavu, A. (2017). Towards urban resilience: A multi-criteria analysis of seismic vulnerability in Iasi City (Romania). Sustainability (Switzerland), 9(2). https://doi.org/10.3390/su9020270

Braithwaite, A., & LI, Q. (2007). Transnational Terrorism Hot Spots: Identification and Impact Evaluation. Conflict Management and Peace Science, 24(4), 281–296. https://doi.org/10.1080/07388940701643623

Ghorbanzadeh, O., Feizizadeh, B., & Blaschke, T. (2018). Multi-criteria risk evaluation by integrating an analytical network process approach into GIS-based sensitivity and uncertainty analyses. Geomatics, Natural Hazards and Risk, 9(1), 127–151. https://doi.org/10.1080/19475705.2017.1413012

Griffiths, G., Johnson, S. D., & Chetty, K. (2017). UK-based terrorists’ antecedent behavior: A spatial and temporal analysis. Applied Geography, 86, 274–282. https://doi.org/10.1016/J.APGEOG.2017.06.007

GTD. (2017). Global Terrorism Database. University of Maryland.

Guo, W., Liu, H., Yu, A., & Li, J. (2016). Research on visual analysis methods of terrorism events. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41, 191–196. https://doi.org/10.5194/isprsarchives-XLI-B2-191-2016

LaFree, G., Dugan, L., Xie, M., & Singh, P. (2012). Spatial and Temporal Patterns of Terrorist Attacks by ETA 1970 to 2007. Journal of Quantitative Criminology, 28(1), 7–29. https://doi.org/10.1007/s10940-011-9133-y

Li, Z., Sun, D., Chen, H., & Huang, S. Y. (2016). Identifying the socio-spatial dynamics of terrorist attacks in the Middle East. IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016, 175–180. https://doi.org/10.1109/ISI.2016.7745463

Maanan, M. M., Maanan, M. M., Rueff, H., Adouk, N., Zourarah, B., & Rhinane, H. (2018). Assess the human and environmental vulnerability for coastal hazard by using a multi-criteria decision analysis. Human and Ecological Risk Assessment: An International Journal, 24(6), 1642–1658. https://doi.org/10.1080/10807039.2017.1421452

Machado, E. R., Valle Júnior, R. F. do, Sanches Fernandes, L. F., & Pacheco, F. A. L. (2018). The vulnerability of the environment to spills of dangerous substances on highways: A diagnosis based on multi criteria modeling. Transportation Research Part D: Transport and Environment, 62, 748–759. https://doi.org/10.1016/J.TRD.2017.10.012

März, S. (2018). Assessing the fuel poverty vulnerability of urban neighbourhoods using a spatial multi-criteria decision analysis for the German city of Oberhausen. Renewable and Sustainable Energy Reviews, 82(2), 1701–1711. https://doi.org/10.1016/j.rser.2017.07.006

Mubarak, Z. (2012). Fenomena Terorisme di Indonesia : Kajian Aspek Teologi, Ideologi dan Gerakan. Jurnal Studi Masyarakat Islam, 15(2), 240–254. https://doi.org/10.11650/tjm.17.2013.3794

National Counter Terrorisme Agency (Badan Nasional Penanggulangan Terorisme). (2018). Indonesia Terrorism Database. National Counter Terrorisme Agency (Badan Nasional Penanggulangan Terorisme).

Nemeth, S. C., Mauslein, J. A., & Stapley, C. (2014). The primacy of the local: Identifying terrorist hot spots using geographic information systems. Journal of Politics, 76(2), 304–317. https://doi.org/10.1017/S0022381613001333

Onat, I. (2016). An analysis of spatial correlates of terrorism using risk terrain modeling. Terrorism and Political Violence, 1–22. https://doi.org/10.1080/09546553.2016.1215309

Onat, I., & Gul, Z. (2018). Terrorism Risk Forecasting by Ideology. European Journal on Criminal Policy and Research, 24(4), 433–449. https://doi.org/10.1007/s10610-017-9368-8

Ottomano Palmisano, G., Govindan, K., Loisi, R. V., Dal Sasso, P., & Roma, R. (2016). Greenways for rural sustainable development: An integration between geographic information systems and group analytic hierarchy process. Land Use Policy, 50, 429–440. https://doi.org/10.1016/j.landusepol.2015.10.016

Python, A., Illian, J., Jones-Todd, C., & Blangiardo, M. (2016). A Bayesian Approach to Modelling Fine-Scale Spatial Dynamics of of Non-State Terrorism: World Study, 2002-2013. ArXiv. https://doi.org/10.1111/rssa.12384

Saaty, T. L. (1989). Group Decision Making and the AHP. In The Analytic Hierarchy Process (pp. 59–67). https://doi.org/10.1007/978-3-642-50244-6_4

Saidi, S., Hosni, S., Mannai, H., Jelassi, F., Bouri, S., & Anselme, B. (2017). GIS-based multi-criteria analysis and vulnerability

method for the potential groundwater recharge delineation, case study of Manouba phreatic aquifer, NE Tunisia. Environmental Earth Sciences, 76(15), 511. https://doi.org/10.1016/j.powtec.2015.10.016

Siqueira, H. E., Pissarra, T. C. T., do Valle Junior, R. F., Fernandes, L. F. S., & Pacheco, F. A. L. (2017). A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances. Environmental Impact Assessment Review, 64, 26–36. https://doi.org/10.1016/j.eiar.2017.02.002

Umar, A. R. M. (2010). Melacak Akar Radikalisme Islam di Indonesia. Jurnal Ilmu Sosial Dan Ilmu Politik, 14(2), 169–186. https://doi.org/10.22146/JSP.10935



DOI: https://doi.org/10.22146/ijg.45691

Article Metrics

Abstract views : 3837 | views : 2726

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2020 Asep Adang Supriyadi, Masita Dwi Mandini Manessa

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

Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)

ISSN 2354-9114 (online), ISSN 0024-9521 (print)

Web Analytics IJG STATISTIC