Analisis Lahan Pertanian Rawan Banjir Menggunakan Metode Multi Atribut Utility Theory Berbasis Sistem Informasi Geografis

Mala Rosa Aprillya, Uswatun Chasanah

Abstract


Jawa Timur memiliki kondisi wilayah yang beragam. Kondisi wilayah tersebut tentunya memiliki potensi bencana yang berdampak signifikan terhadap sektor pertanian. Banjir merupakan salah satu faktor yang merusak lahan pertanian. Manajemen risiko banjir memainkan peran penting dalam membimbing pemerintah dalam membuat keputusan yang tepat waktu dan tepat untuk penyelamatan dan bantuan banjir. Penelitian ini bertujuan untuk mengkaji penilaian risiko banjir pada sektor pertanian di Jawa Timur. Metode Multi Attribute Utility Theory  digunakan untuk memecahkan masalah yang berkaitan dengan penataan ruang dan penanggulangan bencana karena bersifat sistematis dan cocok untuk memecahkan masalah yang kompleks seperti sektor pertanian. Hasil penelitian menunjukkan bahwa wilayah lahan pertanian di Jawa Timur dengan kategori sangat rawan banjir meliputi Kabupaten Bojonegoro, Lamongan, Tuban, dan Sidoarjo. Selanjutnya hasil penelitian ini divisualisasikan dengan pemetaan risiko banjir menggunakan SIG. Hal ini dapat digunakan untuk upaya penanggulangan bencana banjir. Penelitian ini diharapkan dapat membantu pengambilan kebijakan di Dinas Pertanian dan Ketahanan Pangan dalam memantau lahan pertanian yang rawan banjir guna meminimalisir terjadinya bencana banjir di sektor pertanian.


Keywords


Sistem Informasi Geografis; Lahan Pertanian; Multi Attribute Utility theory; Banjir

Full Text:

PDF

References


Applanaidu, S. D., Bakar, N. A., & Baharudin, A. H. (2014). An Econometric Analysis of Food Security and Related Macroeconomic Variables in Malaysia: A Vector Autoregressive Approach (VAR). UMK Procedia, 1(October 2013), 93–102. https://doi.org/10.1016/j.umkpro.2014.07.012

Aprillya, M. R., Suryani, E., & Dzulkarnain, A. (2019). System Dynamics Simulation Model to Increase Paddy Production for Food Security. Journal of Information Systems Engineering and Business Intelligence, 5(1), 67. https://doi.org/10.20473/jisebi.5.1.67-75

Bala, B. K., Bhuiyan, M. G. K., Alam, M. M., Arshad, F. M., Sidique, S. F., & Alias, E. F. (2017). Modelling of supply chain of rice in Bangladesh. International Journal of Systems Science: Operations and Logistics, 4(2), 181–197. https://doi.org/10.1080/23302674.2016.1179813

da Silva, L. B. L., Humberto, J. S., Alencar, M. H., Ferreira, R. J. P., & de Almeida, A. T. (2020). GIS-based multidimensional decision model for enhancing flood risk prioritization in urban areas. International Journal of Disaster Risk Reduction, 48(December 2019). https://doi.org/10.1016/j.ijdrr.2020.101582

Dong, Y., Frangopol, D. M., & Sabatino, S. (2016). Author ’ s Accepted Manuscript. Reliability Engineering and System Safety. https://doi.org/10.1016/j.ress.2016.02.002

Kailiponi, P. (2010). Analyzing evacuation decisions using multi-attribute utility theory (MAUT). Procedia Engineering, 3, 163–174. https://doi.org/10.1016/j.proeng.2010.07.016

Levy, J. K., Hartmann, J., Li, K. W., An, Y., & Asgary, A. (2007). Multi-Criteria Decision Support Systems for Flood Hazard Mitigation and Emergency Response in Urban Watersheds1 JAWRA Journal of the American Water Resources Association Volume 43, Issue 2. JAWRA Journal of the American Water Resources Association, 43(2), 346–358. http://onlinelibrary.wiley.com/doi/10.1111/j.1752-1688.2007.00027.x/abstract

Li, Q., Zhou, J., Liu, D., & Jiang, X. (2012). Research on flood risk analysis and evaluation method based on variable fuzzy sets and information diffusion. Safety Science, 50(5), 1275–1283. https://doi.org/10.1016/j.ssci.2012.01.007

Limbong, T., & Simarmata, J. (2020). Determining Effective Subjects Online Learning (Study and Examination) with Multi-Attribute Utility Theory (MAUT) Method. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 4(2), 370–376. https://doi.org/10.29207/resti.v4i2.1851

Luu, C., von Meding, J., & Mojtahedi, M. (2019). Analyzing Vietnam’s national disaster loss database for flood risk assessment using multiple linear regression-TOPSIS. International Journal of Disaster Risk Reduction, 40(August 2018), 101153. https://doi.org/10.1016/j.ijdrr.2019.101153

Mahbubi, A. (2013). Model Dinamis Supply Chain Beras Berkelanjutan. Jurnal Manajemen Dan Agribisnis, 10(2), 81–89.

Medeiros, C. P., Alencar, M. H., & de Almeida, A. T. (2017). Multidimensional risk evaluation of natural gas pipelines based on a multicriteria decision model using visualization tools and statistical tests for global sensitivity analysis. Reliability Engineering and System Safety, 165(April), 268–276. https://doi.org/10.1016/j.ress.2017.04.002

Muflihah, Y., Setyadi, H. J., Rustanto, I., Dini, N. S., Mardhiana, H., & Pakarbudi, A. (2017). Isu Implementasi Wide Area Network Pada Perusahaan BUMN. 2(April), 18–22. https://doi.org/10.13140/RG.2.2.12759.68008

Naylor, R. L., Battisti, D. S., Vimont, D. J., Falcon, W. P., & Burke, M. B. (2007). Assessing risks of climate variability and climate change for Indonesian rice agriculture. 104(19).

Nurdiawan, O., Putri, H., Studi, P., & Informasi, T. (2014). Pemetaan daerah rawan banjir berbasis sistem informasi geografis dalam upaya mengoptimalkan langkah antisipasi bencana. 1–9.

Pergher, I., & Almeida, A. T. De. (2018). A multi-attribute , rank-dependent utility model for selecting dispatching rules. Journal of Manufacturing Systems, 46, 264–271. https://doi.org/10.1016/j.jmsy.2018.01.007

Stuart, A. M., Devkota, K. P., Sato, T., Pame, A. R. P., Balingbing, C., My Phung, N. T., Kieu, N. T., Hieu, P. T. M., Long, T. H., Beebout, S., & Singleton, G. R. (2018). On-farm assessment of different rice crop management practices in the Mekong Delta, Vietnam, using sustainability performance indicators. Field Crops Research, 229(October), 103–114. https://doi.org/10.1016/j.fcr.2018.10.001

Tanesib, J. L., & Warsito, A. (2018). Pemetaan Daerah Rawan Banjir Dengan Penginderaan Kupang Timur Kabupaten Kupang Provinsi Nusa Tenggara Timur. 3(1), 73–79.

Xiao, Y., Yi, S., & Tang, Z. (2017). Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference. Science of the Total Environment, 599–600, 1034–1046. https://doi.org/10.1016/j.scitotenv.2017.04.218




DOI: http://dx.doi.org/10.30872/jim.v16i2.6554

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer

Editor Informatika Mulawarman Address:
ISSN 1858-4853 (Print) | ISSN 2597-4963 (Online)

Published by: Mulawarman University
Managed by : Informatika Department
Jalan Sambaliung No.9 Sempaja Selatan Samarinda Utara,
Kalimantan Timur 75117
 - Indonesia
E-mail: jim.unmul@gmail.com
OJS: http://e-journals.unmul.ac.id/index.php/JIM
Contact Person: Gubtha Mahendra Putra

 Creative Commons License

Informatika Mulawarman by http://e-journals.unmul.ac.id/index.php/JIM/index is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Under the CC BY-SA license, authors and other users are able to reprint, distribute or use the material for commercial purposes so long as they give attribution to the journal Informatika Mulawarman and license the republished material under the same license.