<![CDATA[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.]]>
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