Integrating fuzzy logic-house of risk for risk mitigation analysis of bondowoso arabica coffee supply chain (a case study in Indonesia)

Authors

DOI:

https://doi.org/10.25186/.v21i.2397

Abstract

Indonesia is one of the largest coffee producers in the world. One of Indonesia's leading Arabica coffee-producing areas is Bondowoso Regency, East Java. UD Barokah is the largest green Arabica coffee processor in Bondowoso Regency. Currently, UD Barokah faces several obstacles in supply chain management that impact the quality of the final processed green Arabica coffee bean product. These obstacles have the potential to cause a risk of loss. Risks that arise in the supply chain can be minimized by carrying out a risk management process to strengthen competitiveness. This study used an integration between the House of Risk (HOR) method and fuzzy logic (FHOR). HOR is used as the main framework for risk mapping and designing mitigation strategies. Meanwhile, the fuzzy approach is applied to accommodate uncertainty and subjectivity in assessing the level of risk importance. The results of the study using FHOR integration for all actors in the supply chain can identify risks in all supply chain actors in detail, from 65 identified risk agents, 31 risk agents are prioritized, and a risk mitigation strategy design is obtained that can be implemented. Risk agents can be mitigated with the most effective and least difficult mitigation strategy approach.

Key words: Supply chain; fuzzy-house of risk; arabica coffee; risk management.

References

Abebe, G. K., Bijman, J., & Royer, A. (2016). Are middlemen facilitators or barriers to improve smallholders' welfare in rural economies? Empirical evidence from Ethiopia. Journal of Rural Studies, 43:203-213.

Abushaega, M. et al. (2021). Design of supply chain network to reduce impacts of damages during shipping. Management and Production Engineering Review, 12:17-26.

Baihaqi, A. et al. (2022). Risk analysis of arabica coffee supply chain in Aceh Tengah Regency, Aceh Province, Indonesia. Coffee Science, 16:e161984.

Emrouznejad, A., Abbasi, S., & Sicakyüz, Ç. (2023). Supply chain risk management: A content analysis-based review of existing and emerging topics. Supply Chain Analytics, 3:100031.

Fadri, R. A. et al. (2020). Production process and quality testing of Arabica ground coffee (Coffee arabica L) Solok Regency, West Sumatera. Journal of Applied Agricultural Science and Technology, 4:36-55.

Farida, I., & Setiawan, D. (2022). Business strategies and competitive advantage: The role of performance and innovation. Journal of Open Innovation: Technology, Market, and Complexity, 8(3):163.

Febrianto, N. A., & Zhu, F. (2023). Coffee bean processing: Emerging methods and their effects on chemical, biological and sensory properties. Food Chemistry, 412:135489.

Ghadge, A., Dani, S., & Kalawsky, R. (2012). Supply chain risk management: Present and future scope. International Journal of Logistics Management, 23(3):313-339.

Ghosh, P., & Venkatachalapathy, N. (2014). Processing and drying of coffee – A review. International Journal of Engineering Research and Technology, 3(2):784-794.

Girma, B. (2024). The impact of packaging and storage on coffee quality: A review. International Journal of Current Research and Academic Review, 12(7):43-49.

Hall, R. D., Trevisan, F., & De Vos, R. C. H. (2021). Coffee berry and green bean chemistry – Opportunities for improving cup quality and crop circularity. Food Research International, 151:110825.

Hanan, A. et al. (2024). Arabica coffee yields at various harvest seasons and altitudes in the Gayo Highlands, Aceh. IOP Conference Series: Earth and Environmental Science, 1297:012001.

Handoyo, S. et al. (2023). A business strategy, operational efficiency, ownership structure, and manufacturing performance: The moderating role of market uncertainty and competition intensity and its implication on open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 9(2):100039.

Herminingsih, H. et al. (2023). The economic benefits of geographical indication (GI) certification for smallholder coffee farmers: A case study in Bondowoso Regency, East Java. Jurnal Ilmiah Respati, 14(1):56-63.

Hoseini, M. et al. (2021). Coffee by-products derived resources. A review. Biomass and Bioenergy, 148:106009.

Hsueh, S. L. et al. (2012). A multi-criteria evaluation model for developmental effectiveness in cultural and creative industries. Procedia Engineering, 29:1755-1761.

Indonesian Central Bureau of Statistics (BPS). (2023). Kabupaten Bondowoso dalam Angka. Jakarta. Indonesia: Central Bureau of Statistics Republic of Indonesia. Available in: <https://bondowosokab.bps.go.id/id/publication/2023/02/28/bad5ab292290dce48ef4e031/kabupaten-bondowoso-dalam-angka-2023.html>

International Coffee Organization - ICO. (2023). Coffee Report and Outlook. Available in: <https://icocoffee.org/documents/cy2023-24/Coffee_Report_and_Outlook_December_2023_ICO.pdf>

Ivanov, D., & Wendler, E. (2017). Natural disasters and supply chain disruption management. In D. Ivanov., & E. Wendler. Chapter 10: Natural disasters and supply chain disruption management. (pp. 245-271).

Isizoh, A. et al. (2012). Temperature control system using fuzzy logic technique. International Journal of Advanced Research in Artificial Intelligence, 1(3):25-30.

Khedr, A. M., & Rani, S. S. Enhancing supply chain management with deep learning and machine learning techniques: A review. Journal of Open Innovation: Technology, Market, and Complexity, 10(4):100379.

Kozarević, S., & Puška, A. (2018). Use of fuzzy logic for measuring practices and performances of supply chain. Operations Research Perspectives, 5:150-160.

Lestari, F. et al. (2020). Supply chain relationship in a downstream sector. Uncertain Supply Chain Management, 8:423-438.

Lin, H., Lin, J., & Wang, F. (2022). An innovative machine learning model for supply chain management. Journal of Innovation & Knowledge, 7(4):100276.

Maccarthy, B. L., Ahmed, W. A. H., & Demirel, G. (2022). Mapping the supply chain: Why, what and how?. International Journal of Production Economics, 250:108688.

Mohammed, H. K., & Knapkova, A. (2016). The impact of total risk management on company's performance. Procedia-Social and Behavioral Sciences, 220:271-277.

Musavi, F. et al. et al. (2024). Identifying and preventing human error in the sugar production process: A multi-stage approach using HTA, HEC and PHEA techniques. Heliyon, 10(9):e29687.

Nguyen, T. T. H. (2024). Measuring supply chain performance using the SCOR model. Operations Research Forum, 5:37.

Ntabe, E. N. et al. (2015). A systematic literature review of the supply chain operations reference (SCOR) model application with special attention to environmental issues. International Journal of Production Economics, 169:310-332.

Onufrey, K., & Bergek, A. (2021). Transformation in a mature industry: The role of business and innovation strategies. Technovation, 105:102190.

Poltronieri, P., & Rossi, F. (2016). Challenges in specialty coffee processing and quality assurance. Challenges, 7(2):19.

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.

Purnomo, B., Ni’maturrakhmat, V., & Wibowo, Y. (2024). System dynamic model of green supply chain management robusta coffee Argopuro in Indonesia: A case study. Coffee Science, 19:e192211.

Purnomo, B., Suryadharma, B., & Al-Hakim, R. (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.

Puspitasari, N., & Yuwono, M. R. A. (2022). Integrating fuzzy logic and house risk method for operational risk management in automotive industry. IOP Conference Series: Earth and Environmental Science, 1098:012007.

Rinaldi, M., & Bottani, E. (2023). How did CORONAVIRUS affect logistics and supply chain processes? Immediate, short and medium-term evidence from some industrial fields of Italy. International Journal of Production Economics, 262:108915.

Santoso, I. et al. (2025). Sustainable coffee supply chain risk mitigation analysis using the Failure Mode and Effect Analysis. BIO Web of Conferences, 165:02002,

Sohl, T., Vroom, G., & Mccann, B. T. (2023). Business model diversification and firm performance: A demand-side perspective. Strategic Entrepreneurship Journal, 14:198-223.

Sudrajat, J., Isytar, I., & Arifin, N. (2021). Farmers' perception and engagement with the role of middlemen: A case study of the vegetable farmers. Makara Human Behavior Studies in Asia, 25(1):45-54.

Tama, Y., Eunike, A., & Hamdala. (2019). Model supply chain agroindustri di Indonesia: Studi kasus produk singkong. Malang: UB Press, 111p.

Tao, S. et al. (2024). Research on inventory sustainable development strategy for maximizing cost-effectiveness in supply chain. Sustainability, 16(11):4442.

Ulfah, M. et al. (2022). Supply-chain risk mitigation with integration house of risk and fuzzy logic: A case study in bakery industry. Journal Industrial Servicess, 8:151.

Ullah, A. A. et al. (2022). Human capital and organizational performance: A moderation study through innovative leadership. Journal of Innovation & Knowledge, 7(4):100261.

United States Department of Agriculture. (2024). Indonesia: Coffee Semi-annual. Available in: <https://www.fas.usda.gov/data/indonesia-coffee-semi-annual-9>.

Wibowo, Y., Purnomo, B., & Kristio, A. (2021). The agroindustry development strategy for Java Ijen-Raung arabica coffee in Bondowoso Regency, East Java. Industria: Jurnal Teknologi dan Manajemen Agroindustri, 10(2):135-148.

Yunanto, Y., & Kristanti, D. (2024). Improving the performance of sustainable human resources in coffee bean supply in the Satak coffee agroindustry, Kediri District. Media Mahardhika, 22:184-197.

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Published

2026-03-12

How to Cite

WIBOWO, Yuli; NI’MATURRAKHMAT, Viko Nurluthfiyadi. Integrating fuzzy logic-house of risk for risk mitigation analysis of bondowoso arabica coffee supply chain (a case study in Indonesia). Coffee Science - ISSN 1984-3909, [S. l.], v. 21, p. e212397, 2026. DOI: 10.25186/.v21i.2397. Disponível em: https://coffeescience2.ufla.br/index.php/Coffeescience/article/view/2397. Acesso em: 20 oct. 2026.