Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science


DOI: 10.5937/jaes0-29797 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 20 article 900 pages: 19-28

T. Brenda Chandrawati*
Universitas Indonesia, Faculty of Engineering, Department of Electrical Engineering, Depok, Indonesia

Anak Agung Putri Ratna
Universitas Indonesia, Faculty of Engineering, Department of Electrical Engineering, Depok, Indonesia

Riri Fitri Sari
Universitas Indonesia, Faculty of Engineering, Department of Electrical Engineering, Depok, Indonesia

A flood is an event of an increase in water volume above the standard limit due to increased rainfall, rising sea levels, storms, and others that result in submerging an area. Floods are disasters that can cause damage and loss of property, disrupt community activities and even cause loss of life. The central defiance to rescue flood victims is choosing a safe route for flood victims to reach the evacuation site. To be able to choose a safe route for flood victims, a flood evacuation simulation is made. Flood evacuation simulation is part of the game that has been created and aims to provide education about the weight of the obstacle that needs to be considered in selecting routes for flood victims. In this flood evacuation simulation, each road has obstacles. The method proposed for choosing safe routes for flood victims is the Fuzzy-based Analytical Hierarchy Process (Fuzzy AHP). The calculation of road route weight using the Fuzzy AHP method will produce the weight for each route. The smallest weight route shows the priority route and the safe route for flood victims to pass. In this case, the Fuzzy AHP method's calculation produces the lowest weight of 0.02347, which is achieved by route 5, the route passing through S-a-b-d-D. This route is a priority route that is safe for flood victims to pass through.

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The author would like obliged to the Ministry of Education and Culture of the Republic of Indonesia through the Directorate General of Research and Development for financial support for this research under the PDD Grant number NKB-22/UN2.RS/HKP.05.00/ 2020

1. Lai, C., Chen, X., Chen, X., Wang, Z., Wu, X., Zhao, S. (2015). A fuzzy comprehensive evaluation model for flood risk based on the combination weight of game theory. Natural Hazards, vol. 77, no. 2, 1243-1259, DOI: 10.1007/s11069-015-1645-6.

2. Bischiniotis, K., de Moel, H., van den Homberg, M., Couasnon, A., Aerts, J., Nobre, G. G., Zsoter, E., van den Hurk, B. (2020). A framework for comparing permanent and forecast-based flood risk-reduction strategies. Science of the total environment, vol. 720, 137572, DOI: 10.1016/j.scitotenv.2020. 137572.

3. Reeve, D., Badr, A. (2003), Performance of sandbags for domestic flood defence, in Proceedings of the Institution of Civil Engineers-Water and Maritime Engineering, vol. 156, no. 4: Thomas Telford Ltd, p. 341-349, DOI: 10.1680/ wame.2003.156.4.341.

4. Lim, M. B. B., Lim Jr, H. R., Piantanakulchai, M. (2019). Flood evacuation decision modeling for high risk urban area in the Philippines. Asia Pacific Management Review, vol. 24, no. 2, 106-113, DOI: 10.1016/j.apmrv.2019.01.001.

5. Saadatseresht, M., Mansourian, A., Taleai, M. (2009). Evacuation planning using multiobjective evolutionary optimization approach. European jour-nal of operational research, vol. 198, no. 1, 305-314, DOI: 10.1016/j.ejor.2008.07.032.

6. Lee, H.-K., Hong, W.-H., Lee, Y.-H. (2019). Experimental study on the influence of water depth on the evacuation speed of elderly people in flood conditions. International journal of disaster risk reduction, vol. 39, 101198, DOI: 10.1016/j.ijdrr. 2019.101198.

7. Nakanishi, H., Black, J., Suenaga, Y. (2019). Investi-gating the flood evacuation behaviour of older people: A case study of a rural town in Japan. Research in Transportation Business & Manage-ment, vol. 30, 100376, DOI: 10.1016/j.rtbm.2019. 100376.

8. Rahmati, O., Pourghasemi, H. R., Zeinivand, H. (2016). Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran. Geocarto International, vol. 31, no. 1, 42-70, DOI: 10.1080/10106049. 2015.1041559.

9. Talha, S., Maanan, M., Atika, H., Rhinane, H. (2019). Prediction of flash flood susceptibility using fuzzy analytical hierarchy process (Fahp) algorithms and Gis: a study case of guelmim region In Southwestern of Morocco. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, 407-414, DOI: 10.5194/isprs-archives-XLII-4-W19-407-2019.

10. Sadek, M., Li, X. (2019). Low-cost solution for assessment of urban flash flood impacts using sentinel-2 satellite images and fuzzy analytic hierarchy process: a case study of ras ghareb city, Egypt. Advances in Civil Engineering, vol. 2019, DOI: 10.1155/2019/2561215.

11. Hoffmann, R., Blecha, D. (2020). Education and disaster vulnerability in Southeast Asia: Evidence and policy implications. Sustainability, vol. 12, no. 4, 1401, DOI: 10.3390/su12041401.

12. Kagawa, F., Selby, D. (2012). Ready for the storm: Education for disaster risk reduction and climate change adaptation and mitigation1. Journal of Education for Sustainable Development, vol. 6, no. 2, 207-217, DOI: 10.1177/0973408212475200.

13. Tsai, M.-H., Wen, M.-C., Chang, Y.-L., Kang, S.-C. (2015). Game-based education for disaster preven-tion. AI & society, vol. 30, no. 4, 463-475, DOI: 10.1007/s00146-014-0562-7.

14. Mokhtar, N., Ismail, A., Muda, Z. (2019). Designing model of serious game for flood safety training. International Journal of Advanced Computer Scien-ce and Applications, vol. 10, no. 5, 331-339, DOI: 10.14569/IJACSA.2019.0100541.

15. Tena-Chollet, F., Tixier, J., Dandrieux, A., Slangen, P. (2017). Training decision-makers: Existing strategies for natural and technological crisis management and specifications of an improved simulation-based tool. Safety science, vol. 97, 144-153, DOI: 10.1016/j.ssci.2016.03.025.

16. Zaini, N. A., Noor, S. F. M., Zailani, S. Z. M. (2020). Design and Development of Flood Disaster Game-based Learning based on Learning Domain. International Journal of Engineering and Advanced Technology vol. 9, no. 4, 679-685, DOI: 10.35940 /ijeat.

17. Tsai, M.-H., Chang, Y.-L., Kao, C., Kang, S.-C. (2015). The effectiveness of a flood protection computer game for disaster education. Visualization in Engineering, vol. 3, no. 1, 9, DOI: 10.1186/ s40327-015-0021-7.

18. Rothkrantz, L. J., Fitrianie, S. (2018). Public Awareness and Education for Flooding Disasters. K. Holla, Ristvej, J., Titko,M (Eds.), Crisis Manage-ment: Theory and Practice. IntechOpen, London, pp. 181-202.

19. Chandrawati, T. B., Ratna, A. A. P., Sari, R. F. (2019), Implementing Bio-Inspired Algorithm for Pathfinding in Flood Disaster Prevention Game, in International Conference on Computational Science and Technology, Kota Kinabalu, Sabah, Malaysia: Springer, p. 23-31, DOI: 10.1007/978-981-15-0058-9_3.

20. Furuichi, M., Aibara, M., Yanagisawa, K. (2014), Design and implementation of serious games for training and education, in UKACC International Conference on Control: IEEE, p. 691-695, DOI: 10.1109/CONTROL.2014.6915223.

21. Saaty, T. L. (2008). Decision making with the analy-tic hierarchy process. International journal of ser- vices sciences, vol. 1, no. 1, 83-98, DOI: 10.1504/ IJSSci.2008.01759.

22. Akbar, M. A., Shameem, M., Khan, A. A., Nadeem, M., Alsanad, A., Gumaei, A. (2020). A fuzzy analy-tical hierarchy process to prioritize the success factors of requirement change management in global software development. Journal of Software: Evolution and Process, e2292, DOI: 10.1002/smr. 2292.

23. Liu, Y., Eckert, C. M., Earl, C. (2020). A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 113738, DOI: 10.1016/j.eswa.2020. 113738.

24. Yang, X.-l., Ding, J.-h., Hou, H. (2013). Application of a triangular fuzzy AHP approach for flood risk evaluation and response measures analysis. Natural Hazards, vol. 68, no. 2, 657-674, DOI: 10.1007/s11069-013-0642-x.

25. Darko, A., Chan, A. P. C., Ameyaw, E. E., Owusu, E. K., Pärn, E., Edwards, D. J. (2019). Review of application of analytic hierarchy process (AHP) in construction. International journal of construction management, vol. 19, no. 5, 436-452, DOI: 10.1080/15623599.2018.1452098.

26. Morgan, R. (2017). An investigation of constraints upon fisheries diversification using the Analytic Hierarchy Process (AHP). Marine Policy, vol. 86, 24-30, DOI: 10.1016/j.marpol.2017.05.037.

27. Singh, R. P., Nachtnebel, H. P. (2016). Analytical hierarchy process (AHP) application for rein-forcement of hydropower strategy in Nepal. Renew-able Sustainable Energy Reviews, vol. 55, 43-58, DOI: 10.1016/j.rser.2015.10.138.

28. Thanki, S., Govindan, K., Thakkar, J. (2016). An investigation on lean-green implementation practices in Indian SMEs using analytical hierarchy process (AHP) approach. Journal of Cleaner Production, vol. 135, 284-298, DOI: 10.1016/ j.jclepro.2016.06.105.

29. Davarpanah, S., Bonab, S. H., Khodaverdizadeh, M. (2016). Assessment and comparison of sustainable agriculture approach using a combination of AHP and TOPSIS. International Academic Journal of Economics, vol. 3, no. 9, 7-18.

30. Quoc, N. K., Prakash, I., Pham, B. T. (2019). Agricultural land suitability analysis for Yen Khe Hills (NgheAn, Vietnam) using analytic hierarchy process (AHP) combined with geographic information systems (GIS). Indian Journal of Ecology, vol. 46, no. 3, 445-454.

31. Rukanee, D., Sangchan, S., Choomjaihan, P. (2020). Assessment of the suitability of land use for agriculture by analytical hierarchy process: AHP in lower Prachinburi watershed, eastern Thailand. Agricultural Engineering International: CIGR Journal, vol. 22, no. 3, 19-26.

32. Romero-Gelvez, J. I., Beltrán-Fernández, S. V., Aristizabal, A. J., Zapata, S., Castañeda, M. (2020), Precision Agriculture Technology Evaluation using Combined AHP and GRA for Data Acquisition in Apiculture, in Workshops at the Third International Conference on Applied Informatics 2020, Ota, Nigeria.

33. Sajadian, M., Khoshbakht, K., Liaghati, H., Veisi, H., Damghani, A. M. (2017). Developing and quantifying indicators of organic farming using analytic hierarchy process. Ecological Indicators, vol. 83, 103-111, DOI: 10.1016/j.ecolind.2017.07.047.

34. Chakraborty, A., Joshi, P. (2016). Mapping disaster vulnerability in India using analytical hierarchy process. Geomatics, Natural Hazards and Risk, vol. 7, no. 1, 308-325, DOI: 10.1080/19475705.2014. 897656.

35. Kumar, R., Anbalagan, R. (2016). Landslide susceptibility mapping using analytical hierarchy process (AHP) in Tehri reservoir rim region, Uttarakhand. Journal of the Geological Society of India, vol. 87, no. 3, 271-286, DOI: 10.1007/s12594-016-0395-8.

36. Kubler, S., Robert, J., Derigent, W., Voisin, A., Le Traon, Y. (2016). A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications. Expert Systems with Applications, vol. 65, 398-422, DOI: 10.1016/j.eswa.2016.08.064.

37. Mangla, S. K., Kumar, P., Barua, M. K. (2015). Risk analysis in green supply chain using fuzzy AHP approach: A case study. Resources, Conservation and Recycling, vol. 104, 375-390, DOI: 10.1016/ j.resconrec.2015.01.001.

38. Leśniak, A., Kubek, D., Plebankiewicz, E., Zima, K., Belniak, S. (2018). Fuzzy AHP application for supporting contractors’ bidding decision. Symmetry, vol. 10, no. 11, 642, DOI: 10.3390/sym10110642.

39. Polat, G., Eray, E., Bingol, B. N. (2017). An integrated fuzzy MCGDM approach for supplier selection problem. Journal of Civil Engineering and Management, vol. 23, no. 7, 926-942, DOI: 10.3846/13923730.2017.1343201.

40. Huang, B.-W., Yang, Y.-C. (2018). Evaluation Indicators and Development Strategies of Agricultural Revitalization for Rural Rejuvenation. Journal of Reviews on Global Economics, vol. 7, 269-279, DOI: 10.6000/1929-7092.2018.07.24.

41. Sari, D. P., Anwar, N., Sidharti, T. S. (2019). Analysis of Irrigation Modernization Pillars with Fuzzy Analytical Hierarchy Process (FAHP) Approachment.

42. Wijitkosum, S. (2018). Fuzzy AHP for drought risk assessment in Lam Ta Kong watershed, the north-eastern region of Thailand. Soil and Water Research, vol. 13, no. 4, 218-225, DOI: 10.17221/ 158/2017-SWR.

43. Deng, F., Zhang, X., Liang, X., Guo, Z., Bao, C. (2016), Earthquake disaster emergency supply chain performance evaluation based on triangular fuzzy numbers, in 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM): IEEE, p. 1483-1487, DOI: 10.1109/IEEM.2016.7798124.

44. Sabah, L., Yücedag, I., Yalcin, C. (2017). Earthquake Hazard Analysis for Districts of Düzce via AHP and Fuzzy Logic Methods. Cognitive Systems, vol. 2, no. 1.

45. Timperio, G., Panchal, G. B., Samvedi, A., Goh, M., De Souza, R. (2017). Decision support framework for location selection and disaster relief network design. Journal of Humanitarian Logistics and Supply Chain Management, DOI: 10.1108/JHLSCM -11-2016-0040.

46. Kerkez, M., Gajović, V., Puzić, G. (2017). Flood risk assessment model using the fuzzy analytic hierarchy process. Progress in Economic Sciences, vol. 4, 271-282, DOI: 10.14595/PES/04/019.

47. Zou, Q., Zhou, J., Zhou, C., Song, L., Guo, J. (2013). Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP. Stochastic Environmental Research Risk Assessment, vol. 27, no. 2, 525-546, DOI: 10.1007/ s00477-012-0598-5.

48. Semarang, D. P. R. K. One Map Semarang, from, accessed on 2021-05-21.

49. Chandrawati, T. B., Ratna, A. A. P., Sari, R. F. (2020). Path Selection using Fuzzy Weight Aggregated Sum Product Assessment. International Journal of Computers, Communications & Control, vol. 15, no. 5, DOI: 10.15837/ijccc.2020.5.3978.

50. Helderop, E., Grubesic, T. H. (2019). Flood evacuation and rescue: The identification of critical road segments using whole-landscape features. Transportation research interdisciplinary perspectives, vol. 3, 100022, DOI: 10.1016/j.trip. 2019.100022.

51. Alonso, J. A., Lamata, M. T. (2006). Consistency in the analytic hierarchy process: a new approach. International journal of uncertainty, fuzziness and knowledge-based systems, vol. 14, no. 04, 445-459.

52. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, vol. 8, no. 3, 338-353, DOI: 10.1016/S0019-9958(65)90241-X.

53. Chang, D.-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European journal of operational research, vol. 95, no. 3, 649-655, DOI: 10.1016/0377-2217(95)00300-2.