Mitigasi Rantai Pasok Rumput Laut dengan Pendekatan House of Risk dan Fuzzy AHP di Kabupaten Maluku Tenggara

https://doi.org/10.22146/agritech.27770

Wellem Anselmus Teniwut(1*), Kamilius Deleles Betaubun(2), Marimin Marimin(3), Taufik Djatna(4)

(1) Program Studi Agribisnis Perikanan, Politeknik Perikanan Negeri Tual, Jl. Raya Langgur-Sathean Km. 7, Langgur, Kabupaten Maluku Tenggara, 97611
(2) Program Studi Agribisnis Perikanan, Politeknik Perikanan Negeri Tual, Jl. Raya Langgur-Sathean Km. 7, Langgur, Kabupaten Maluku Tenggara, 97611
(3) Departemen Teknologi Industri Pertanian, Fakultas Teknologi Pertanian, Institut Pertanian Bogor, Jl. Lingkar Akademik, Jawa Barat 16680
(4) Departemen Teknologi Industri Pertanian, Fakultas Teknologi Pertanian, Institut Pertanian Bogor, Jl. Lingkar Akademik, Jawa Barat 16680
(*) Corresponding Author

Abstract


Seaweed is among fishery commodities with great potential economy prospect. Southeast Maluku District is one of the main producers in Eastern region of Indonesia. Despite the high production since 2012, the number of farmers and the product has declined due to inadequate supply chain coordination and information dissemination among members. Therefore, this study aimed to mitigate the assymetric information in the region using the house of risk (HOR) to identify the risks to be addressed, and also provide response on the source of supply chain risk. Furthermore, Analytic hierarchy process (AHP) with fuzzy approach was used to determine the major factor, and then choose the best alternative to mitigate asymmetric information in the supply chain. Results showed there were five factors that contributed 70% risks. The results also indicated that dependence on local distributor was a factor that had to be prioritized and addressed. In addition, to mitigate the operational risks, findings showed it is necessary to establish seaweed farmers forum, which is the best approach based on the cost and effectiveness. This study also stated that local ,government of Southeast Maluku District was the main actor that helps to overcome the risks and asymmetric information problem. Therefore, the best alternative was to form an information center for seaweed cultivation, which will provide the knowledge of prices and potential buyer outside the region.


Keywords


Asymmetric information; risks mitigation; seaweed; supply chain



References

Ahmadi, M., Behzadian, K., Ardeshir, A., & Kapelan, Z. (2017). Comprehensive risk management using fuzzy FMEA and MCDA techniques in highway construction projects. Journal of Civil Engineering and Management. https://doi.org/10.3846/13923730.2015.1068847

Akpabio, I. A., & Inyang, E. B. (2007). Major constraints affecting aquaculture development in Akwa Ibom State, Nigeria. African Journal of Aquatic Science. https://doi.org/10.2989/AJAS.2007.32.1.7.144

Ayaǧ, Z., & Özdemir, R. G. (2006). A fuzzy AHP approach to evaluating machine tool alternatives. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-005-6635-1

Bixler, H. J., & Porse, H. (2011). A decade of change in the seaweed hydrocolloids industry. Journal of Applied Phycology. https://doi.org/10.1007/s10811-010-9529-3

Boute, R., Manage-, T., Lambrecht, M., & Management, I. (2007). Altruistic Behavior in Supply Chain Management. Review of Business and Economic Literature, LII(3), 499–516.

Crawford, B. (2002). Seaweed Farming: An Alternative Livelihood for Small-Scale Fishers? In Coastal Resources Center.

Diana, J. S., Egna, H. S., Chopin, T., Peterson, M. S., Cao, L., Pomeroy, R., Verdegem, M., Slack, W. T., Bondad-Reantaso, M. G., & Cabello, F. (2013). Responsible aquaculture in 2050: Valuing local conditions and human innovations will be key to success. BioScience. https://doi.org/10.1525/bio.2013.63.4.5

DKP Kabupaten Maluku Tenggara. (2016). Laporan Statistik Perikanan Budidaya Kabupaten Maluku Tenggara Tahun 2015. Dinas Kelautan dan Perikanan Kabupaten Maluku Tenggara.

Doukidis, G. I., Matopoulos, A., Vlachopoulou, M., Manthou, V., & Manos, B. (2007). A conceptual framework for supply chain collaboration: Empirical evidence from the agri-food industry. Supply Chain Management: An International Journal. https://doi.org/10.1108/13598540710742491

Ganguly, K. K., & Guin, K. K. (2013). A fuzzy AHP approach for inbound supply risk assessment. Benchmarking. https://doi.org/10.1108/14635771311299524

Gordon, D. V., & Hussain, S. (2015). Price Determination and Demand Flexibilities in the Ex-Vessel Market for Tuna in the Republic of Maldives. Aquaculture Economics and Management. https://doi.org/10.1080/13657305.2015.994234

Gunasekaran, A., Williams, H. J., & McGaughey, R. E. (2005). Performance measurement and costing system in new enterprise. Technovation. https://doi.org/10.1016/S0166-4972(03)00176-7

Huang, G. Q., Lau, J. S. K., & Mak, K. L. (2003). The impacts of sharing production information on supply chain dynamics: A review of the literature. In International Journal of Production Research. https://doi.org/10.1080/0020754031000069625

Huang, S., & Yang, J. (2016). Information acquisition and transparency in a supply chain with asymmetric production cost information. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2016.10.005

Jang, W., & Klein, C. M. (2011). Supply chain models for small agricultural enterprises. Annals of Operations Research. https://doi.org/10.1007/s10479-009-0521-8

Landazuri-Tveteraas, U., Asche, F., Gordon, D. V., & Tveteraas, S. L. (2018). Farmed fish to supermarket: Testing for price leadership and price transmission in the salmon supply chain. Aquaculture Economics and Management. https://doi.org/10.1080/13657305.2017.1284943

Lei, Q., Chen, J., Wei, X., & Lu, S. (2015). Supply chain coordination under asymmetric production cost information and inventory inaccuracy. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2015.09.015

Lyon, F. (2003). Community groups and livelihoods in remote rural areas of Ghana: How small-scale farmers sustain collective action. Community Development Journal. https://doi.org/10.1093/cdj/38.4.323

Marsden, T., Banks, J., & Bristow, G. (2000). Food supply chain approaches: Exploring their role in rural development. Sociologia Ruralis. https://doi.org/10.1111/1467-9523.00158

Marimin, M. N., Suharjito, H. S., Utama, D. N., Astuti, R., & Martini, S. (2013). Teknik dan analisis pengambilan keputusan fuzzy dalam manajemen rantai pasok. Bogor: IPB Press.

Marimin dan Maghfiroh N. (2010). Aplikasi Teknik Pengambilan Keputusan Dalam Manajemen Rantai Pasok. Bogor: IPB Press.

Mau, N., & Mau, M. (2009). Securing global food distribution networks. In International Series in Operations Research and Management Science. https://doi.org/10.1007/978-0-387-79934-6_20

Pujawan, I. N., & Geraldin, L. H. (2009). House of risk: A model for proactive supply chain risk management. Business Process Management Journal, 15(6), 953–967. https://doi.org/10.1108/14637150911003801

Robledo, D., Gasca-Leyva, E. & Fraga, J. (2013). Social and economic dimensions of carrageenan seaweed farming in Mexico. In D. Valderrama, J. Cai, N. Hishamunda & N. Ridler, eds. Social and economic dimensions of carrageenan seaweed farming, pp. 185– 204. Fisheries and Aquaculture Technical Paper No. 580. Rome, FAO. 204 pp.

Samvedi, A., Jain, V., & Chan, F. T. S. (2013). Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS. International Journal of Production Research. https://doi.org/10.1080/00207543.2012.741330

Sapkota, P., Dey, M. M., Alam, M. F., & Singh, K. (2015). Price Transmission Relationships along the Seafood Value Chain in Bangladesh: Aquaculture and Capture Fisheries. Aquaculture Economics and Management. https://doi.org/10.1080/13657305.2015.994237

Septiani, W., & Djatna, T. (2015). Rancangan Model Performansi Risiko Rantai Pasok Agroindustri Susu dengan Menggunakan Pendekatan Logika Fuzzy. Agritech.

Sievanen, L., Crawford, B., Pollnac, R., & Lowe, C. (2005). Weeding through assumptions of livelihood approaches in ICM: Seaweed farming in the Philippines and Indonesia. Ocean and Coastal Management. https://doi.org/10.1016/j.ocecoaman.2005.04.015

Suharjito., Machfud., Haryanto, B., & Marimin. (2011). Pemodelan optimasi mitigasi risiko rantai pasok produk/komoditas Jagung. Agritech, 31(3), 215–227. https://doi.org/10.22146/agritech.9747

Taylan, O., Bafail, A. O., Abdulaal, R. M. S., & Kabli, M. R. (2014). Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing Journal. https://doi.org/10.1016/j.asoc.2014.01.003

Teniwut, W. A., Kabalmay, J. (2014). Studi Empiris : EValuasi usaha budidaya rumput laut di kabupaten maluku tenggara. Prosiding Seminar Ilmiah Tahunan Ke-2 Tahun 2014 “Perikanan dan Pembangunan,” 55–60.

Teniwut, W. A. (2016). For sustainable revenue of fisheries sector in small islands: Evidence of Maluku, Indonesia. AACL Bioflux. https://doi.org/10.5281/zenodo.245507

Tsolakis, N. K., Keramydas, C. A., Toka, A. K., Aidonis, D. A., & Iakovou, E. T. (2014). Agrifood supply chain management: A comprehensive hierarchical decision-making framework and a critical taxonomy. In Biosystems Engineering. https://doi.org/10.1016/j.biosystemseng.2013.10.014



DOI: https://doi.org/10.22146/agritech.27770

Article Metrics

Abstract views : 1047 | views : 1321

Refbacks

  • There are currently no refbacks.




Copyright (c) 2020 Agritech

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

agriTECH has been Indexed by:


agriTECH (print ISSN 0216-0455; online ISSN 2527-3825) is published by Faculty of Agricultural Technology, Universitas Gadjah Mada in colaboration with Indonesian Association of Food Technologies.


website statisticsView My Stats