Analisis Risiko Rantai Pasok Peternakan Ayam Petelur Menggunakan House of Risk dan Interpretive Structural Modelling
Abstract
The study aims to formulate risk mitigation strategies for the supply chain of laying hen farms CV. XYZ using the House of Risk (HOR) and Interpretive Structural Modeling (ISM) methods. HOR is used to identify risks and calculate aggregate risk potential (ARP), resulting in eight mitigation strategies based on the effectiveness value against the difficulty of implementation (ETD) such as administrative standardization (ETD 9526) and quality-based supplier evaluation (8088), and installation of temperature & humidity sensors (6438). ISM is used to compile the relationships and priorities for strategy implementation. The results show that the combination of HOR and ISM is effective in designing risk mitigation. The limitations of this study lie in the focus only on CV. XYZ and data obtained from internal interviews, so the results do not necessarily represent the entire laying hen farm industry.
References
Ahmad, Kosasih, W., Kristina, H. J., Widodo, L., & Pasaribu, K. (2020). Mitigation of supply chain risk using HOR model at PT. Sumber Karya Indah. IOP Conference Series: Materials Science and Engineering, 847(1), 1–8. https://doi.org/10.1088/1757-899X/847/1/012059.
Ahmad, N., & Qahmash, A. (2021). Smartism: Implementation and assessment of interpretive structural modeling. Sustainability (Switzerland), 13(16), 1–27. https://doi.org/10.3390/su13168801.
Albana, A. S., Prihadianto, R. D., & Mardhiana, H. (2022). Framework development for the assessment of the supply chain resilience using the house of risk. Indonesian Journal of Business and Entrepreneurship, 8(2), 304–312. http://dx.doi.org/10.17358/IJBE.8.2.304.
Amade, B. (2021). An interpretive structural modeling approach to enablers of green supply chain management on construction projects. Journal of Project Management (Canada), 6(2), 73–82. https://doi.org/10.5267/j.jpm.2021.1.003.
Amini, A., & Alimohammadlou, M. (2021). Toward equation structural modeling: An integration of interpretive structural modeling and structural equation modeling. Journal of Management Analytics, 8(4), 693–714. https://doi.org/10.1080/23270012.2021.1881927.
Bagherpour, M., Zadeh, M. K., Mahmoudi, A., & Deng, X. (2020). Interpretive structural modeling in earned value management. Journal of Civil Engineering and Management, 26(6), 524–533. https://doi.org/10.3846/jcem.2020.12182.
Cerar, J., Nell, P. C., & Reiche, B. S. (2021). The declining share of primary data and the neglect of the individual level in international business research. Journal of International Business Studies, 52(7), 1365–1374. https://doi.org/10.1057/s41267-021-00451-0.
Chakraborty, A., Amin, M. A., & Baldacci, R. (2023). Analysis of internal factors of green supply chain management: An interpretive structural modeling approach. Cleaner Logistics and Supply Chain, 7(January), 100099. https://doi.org/10.1016/j.clscn.2023.100099.
Cilingir, Z. uk., Basfirinci, C., & Mitra, A. (2022). Weighted Interpretive structural modeling for supply chain risk management: An application to logistics service providers in Turkey. Logistics, 6(3), 1–22. https://doi.org/10.3390/logistics6030057.
Fradinata, E., Zulfiadi, & Arhami. (2025). Risk mitigation analysis with the house of risk (HOR) method approach in the service procurement process. Enrichment: Journal of Multidisciplinary Research and Development, 3(3), 513–529. https://journalenrichment.com/index.php/jr/%0A.
Haswika, Mansur, A., & Maghfiroh, M. F. N. (2024). Risk mitigation strategies for sustainable poultry supply chain management. Advance Sustainable Science Engineering and Technology, 6(4), 02403011. https://doi.org/10.26877/asset.v6i4.997.
Hughes, D. L., Rana, N. P., & Dwivedi, Y. K. (2020). Elucidation of IS project success factors: An interpretive structural modelling approach. Annals of Operations Research, 285(1–2), 35–66. https://doi.org/10.1007/s10479-019-03146-w.
Ilham, N., & Yusdja, Y. (2010). Dampak flu burung terhadap produksi unggas dan kontribusi usaha unggas terhadap pendapatan peternak skala kecil di Indonesia. Jurnal Agro Ekonom, 28(1), 39–68. https://doi.org/10.21082/jae.v28n1.2010.39-68.
Jalili-Firoozinezhad, S., Filippi, M., Mohabatpour, F., Letourneur, D., & Scherberich, A. (2020). Chicken egg white: Hatching of a new old biomaterial. Materials Today, 40(November), 193–214. https://doi.org/10.1016/j.mattod.2020.05.022.
Jin, Y. H., Lee, K. T., Lee, W. I., & Han, Y. K. (2011). Effects of storage temperature and time on the quality of eggs from laying hens at peak production. Asian-Australasian Journal of Animal Sciences, 24(2), 279–284. https://doi.org/10.5713/ajas.2011.10210.
Junus, R., & Baihaqi, I. (2025). Supply chain risk analysis in wholesale pharmaceutical trading companies using the house of risk (HOR) method. Journal of Applied Sciences, Management and Engineering Technology, 6(1), 57–68. https://doi.org/10.31284/j.jasmet.2025.v6i1.7253.
Kurniawan, S., Marzuky, D., Ryanto, R., & Agustine, V. (2021). Risk and supply chain mitigation analysis using house of risk method and analytical network process (A case study on palm oil company). The Winners, 22(2), 123–136. https://doi.org/10.21512/tw.v22i2.7056.
Małyjurek, S. K. (2022). Interpretive structural modelling of inter-agency collaboration risk in public safety networks. Quality and Quantity, 56(3), 1193–1221. https://doi.org/10.1007/s11135-021-01172-0.
Natalia, C., Hutapea, Y. F. T. B., Oktavia, C. W., & Hidayat, T. P. (2020). Interpretive structural modeling and house of risk implementation for risk association analysis and determination of risk mitigation strategy. Jurnal Ilmiah Teknik Industri, 19(1), 10–21. https://doi.org/10.23917/jiti.v19i1.9014.
Natalia, C., Oktavia, C. W., Hidayat, T. P., & Makatita, W. (2020). Risk management model development by integrating house of risk model and ANP model. Journal of Administrative and Business Studies, 6(4), 138–149. https://doi.org/10.20474/jabs-6.4.4.
Oktavera, R., Kurniawan, M. R., Saraswati, R., & Sutejo, B. (2022). Risk management analysis in tobacco supply chain using the house of risk method. Journal of Applied Science, Engineering, Technology, and Education, 4(2), 167-175. https://doi.org/10.35877/454RI.asci844.
Palit, T., Bari, A. B. M. M., & Karmaker, C. L. (2022). An integrated principal component analysis and interpretive structural modeling approach for electric vehicle adoption decisions in sustainable transportation systems. Decision Analytics Journal, 4(August), 100119. https://doi.org/10.1016/j.dajour.2022.100119.
Paputungan, I. V., Faruq, A. Al, Puspasari, F., Hakim, F. Al, Fahrurrozi, I., Oktiawati, U. Y., & Mutakhiroh, I. (2020). Temperature and humidity monitoring system in broiler poultry farm. IOP Conference Series: Materials Science and Engineering, 803(1), 1–6. https://doi.org/10.1088/1757-899X/803/1/012010.
Perdana, S., Usman, R., & Arifiya, N. (2020). Analysis of supply chain risk mitigation strategies in the Bogor compressor company with the house of risk method. IOP Conference Series: Materials Science and Engineering, 852(1), 1–6. https://doi.org/10.1088/1757-899X/852/1/012094.
Purnomo, B. H., Suryadharma, B., & Al-Hakim, R. G. (2021). Risk mitigation analysis in a supply chain of coffee using house of risk method. Industria: Jurnal Teknologi Dan Manajemen Agroindustri, 10(2), 111–124. https://doi.org/10.21776/ub.industria.2021.010.02.3.
Purwaningsih, R., Ramadani, I., Hartini, S., Aisyah, A., & Putri, A. (2021). Supply chain risk assessment at poultry slaughterhouses using house of risk method to define mitigation action. Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management, 14(16), 2973–2982. http://ieomsociety.org/proceedings/2021indonesia/551.pdf.
Ramos, E., Pettit, T. J., Habib, M., & Chavez, M. (2021). A model ISM-MICMAC for managing risk in agri-food supply chain: An investigation from the Andean region of Peru. International Journal of Value Chain Management, 12(1), 62–85. https://doi.org/10.1504/IJVCM.2021.112845.
Rani, H. A., Amin, J., Syuhada, R., Mubarak, M. H., & Shafly Aqsha, M. (2024). Enhancing supply chain management risk mitigation: A house of risk methodology applied to brick manufacturing in Aceh Besar Regency. Qeios, 4(1), 1–22. https://doi.org/10.32388/fsjf2f.2.
Sarikhani, Y., Shojaei, P., Rafiee, M., & Delavari, S. (2020). Analyzing the interaction of main components of hidden curriculum in medical education using interpretive structural modeling method. BMC Medical Education, 20(1), 1–9. https://doi.org/10.1186/s12909-020-02094-5.
Senadhilankara, P., Korale-Gedara, P., & Perera, W. N. U. (2024). Risk perception, management strategies, determinants of adoption and sustainability in Sri Lanka’s layer chicken farming industry: Navigating crisis. Sage Journals, 34(1), 35–51. https://doi.org/10.1177/10185291241297440.
Shaukat, M. Z., Niazi, A. A. K., Qazi, T. F., & Basit, A. (2021). Analyzing the underlying structure of online teaching during the COVID-19 pandemic period: An empirical investigation of issues of students. Frontiers in Psychology, 12(April), 1–12. https://doi.org/10.3389/fpsyg.2021.605138.
Syamsiyah, N., Qanti, S. R., & Rochdiani, D. (2024). Risk mitigation in environmental conservation for potato production in Cisangkuy Sub-Watershed, Bandung Regency, West Java, Indonesia. Agriculture (Switzerland), 14(10), 1–21. https://doi.org/10.3390/agriculture14101726.
Wicaksono, D., & Kamal, T. (2020). Micro climate monitoring system in closed broiler cages based on the internet of things. Jurnal Teknologi Dan Sistem Komputer, 8(2), 100–105. https://doi.org/10.14710/jtsiskom.8.2.2020.100-105.
Windrawati, R., Susrusa, K. B., & Ambarawati, I. G. A. A. (2022). Supply chain management performance on laying chicken farm. International Journal of Business, Economics & Management, 5(4), 496–503. https://doi.org/10.21744/ijbem.v5n4.2056.
Yang, N. (2021). Egg production in China: Current status and outlook. Frontiers of Agricultural Science and Engineering, 8(1), 25–34. https://doi.org/10.15302/J-FASE-2020363.
Zhang, H., Wu, X., & Ju, M. (2024). Developing a cognitive model of solid geometry based on interpretive structural modeling method. Heliyon, 10(5), e27063. https://doi.org/10.1016/j.heliyon.2024.e27063.
Copyright (c) 2025 Khabib Fahruddin, Farida Pulansari
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
