Penerapan Analisis sensitivitas dalam Pengambilan Keputusan Operasional

Authors

  • Fadhilah Rahmah Universitas Islam Negeri Sumatera Utara
  • Ekki Wahyuni Lubis Universitas Islam Negeri Sumatera Utara
  • Winda Winata S Pane Universitas Islam Negeri Sumatera Utara
  • Abdullah Nasution Universitas Islam Negeri Sumatera Utara
  • Siti Salamah Br Ginting Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.62383/aktivisme.v2i3.1106

Keywords:

Sensitivity-analysis, linear-programming, optimization

Abstract

This study aims to systematically review the application of sensitivity analysis in operational decision-making based on linear programming. The research method used is a Systematic Literature Review (SLR), analyzing scientific articles published between 2018 and 2024 from databases such as Scopus, ScienceDirect, SpringerLink, and Google Scholar. The review focuses on how sensitivity analysis is employed to evaluate the stability of linear programming solutions in the face of parameter changes, such as objective function coefficients, constraint bounds, and resource availability. The results indicate that local sensitivity analysis approaches are the most commonly used due to their simplicity and ease of interpretation. However, they fall short in capturing parameter interactions and complex uncertainty. Therefore, recent studies have started to explore global sensitivity methods, such as Morris and Sobol techniques, as well as geometric visualization approaches to provide a more holistic understanding. This study recommends integrating both local and global approaches and utilizing computational tools to enhance the robustness of operational decisions. The findings are expected to serve as a reference for more adaptive, efficient, and resilient decision-making under uncertainty.

Downloads

Download data is not yet available.

References

A practical approach to sensitivity analysis in linear programming. (2010). ScienceDirect. https://www.sciencedirect.com

Ahmed, S., Sultana, J., Yeasmin Nilu, T., & Islam, S. (2021). Sensitivity analysis of linear programming in decision making model. International Journal of Theoretical and Applied Mathematics, 7(3), 53–56. https://www.sciencepublishinggroup.com

Andriani, R., & Yuliana, S. (2020). Implementasi analisis sensitivitas pada masalah maksimisasi keuntungan produksi roti di CV Lyly Bakery. Jurnal Matematika, Statistika dan Komputasi, 16(1), 65–72.

Anis, F. (2021). Analisis sensitivitas pada pemrograman linear untuk menentukan produksi optimal di PT Dae Gil Indonesia. Jurnal Ekonomi dan Bisnis, 12(2), 45–52.

Auliya, N. F. (2022). Analisis sensitivitas terhadap model transportasi menggunakan metode MODI dan Stepping Stone (Skripsi). Universitas Islam Negeri Maulana Malik Ibrahim Malang.

Confalonieri, R., et al. (2010). Enhanced Morris method for global sensitivity analysis: Good proxy for Sobol index. Structural and Multidisciplinary Optimization. https://dl.acm.org

Iooss, B., & Lemaître, P. (2014). A review on global sensitivity analysis methods. arXiv. https://arxiv.org

Kaci, M., & Radjef, S. (2023). A new geometric approach for sensitivity analysis in linear programming. arXiv. https://arxiv.org

Morris, M. D. (1991). Factorial sampling plans for preliminary computational experiments. In Global Sensitivity Analysis: The Primer (2007). Dijelaskan ulang dalam Saltelli et al. https://en.wikipedia.org

Neto, C., et al. (2024). Linear programming sensitivity measured by the optimal value worst-case derivative. Taylor & Francis. https://www.tandfonline.com

Rackauckas, C. (2020). Global sensitivity analysis – Primer & methods. MIT. https://book.sciml.ai

Rahmawati, D., & Prasetyo, A. (2018). Aplikasi analisis sensitivitas dalam linear programming untuk penjadwalan produksi di industri garmen. Dalam Prosiding Seminar Nasional Matematika dan Pendidikan Matematika (SENAMA), Universitas Negeri Yogyakarta.

Rizki, M. N., & Lestari, R. (2019). Pemanfaatan analisis sensitivitas dalam linear programming untuk optimalisasi produksi usaha mikro. Jurnal MIPA Terapan dan Sains, 7(1), 32–39.

Robust combination of the Morris and Sobol methods in complex systems. (2019). ScienceDirect. https://www.sciencedirect.com

Sensitivity analysis in linear programming: Just be careful! (1996). ScienceDirect. https://www.sciencedirect.com

Sobol’, I. M. (1993). Sensitivity estimates for non linear mathematical models. Mathematical Modelling & Computational Experiment, 1, 407–414. https://en.wikipedia.org

Sobol’, I. M. (2001). Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation, 55(1–3), 271–280. https://en.wikipedia.org

Ward, J. E., & Wendell, R. E. (1990). Approaches to sensitivity analysis in linear programming. Annals of Operations Research, 27, 3–38. https://link.springer.com

Xu, G., & Burer, S. (2015). Robust sensitivity analysis of the optimal value of linear programming. arXiv. https://arxiv.org

Yeasmin Nilu, T., Ahmed, S., & Bhuiyan, M. A. I. (2017). A study of sensitivity analysis in linear programming problem and its implementation in real life. Green University Press. https://www.researchgate.net

Downloads

Published

2025-06-23

How to Cite

Fadhilah Rahmah, Ekki Wahyuni Lubis, Winda Winata S Pane, Abdullah Nasution, & Siti Salamah Br Ginting. (2025). Penerapan Analisis sensitivitas dalam Pengambilan Keputusan Operasional. Aktivisme: Jurnal Ilmu Pendidikan, Politik Dan Sosial Indonesia, 2(3), 264–270. https://doi.org/10.62383/aktivisme.v2i3.1106