This paper investigates the application of robust optimization to enhance portfolio strategies for Indonesian banking stocks, addressing the limitations of classical mean-variance optimization under market uncertainty. It compares moving-window and bootstrapping methods for constructing uncertainty sets, demonstrating that the moving-window approach offers a better risk-return trade-off, particularly for risk-tolerant investors.