Abstract—The rapid development of Islamic tourism demands a decision-making model capable of integrating economic, environmental, and religious dimensions within a balanced analytical framework. This study refines the Multi-Objective Preference Analysis (MOPA) method by introducing a min–max linear normalization approach to improve ranking proportionality and sensitivity in multi-criteria evaluation. Using empirical data from 18 Islamic tourism destinations in North Sumatra and eight benefit type criteria, the improved MOPA demonstrates wider score dispersion (0.221–0.840) and stronger ranking discrimination than classical MCDA methods (Analytic Hierarchy Process, Simple Additive Weighting, Technique for Order Preference by Similarity to Ideal Solution, Multi-Objective Optimization on the basis of Ratio Analysis). Statistical validation confirms the robustness of the model, with ANOVA (p = 0.038, η² = 0.62) showing significant improvement and Spearman’s correlation (ρ = 0.91) indicating high consistency across methods. Sensitivity analysis under ±5–10% weight variation achieves ranking stability above 90%, confirming robustness to subjective bias. Furthermore, the operationalization of Sharia compliance indicators halal certification, mosque accessibility, and regional policy support translates ethical and spiritual values into measurable criteria, strengthening the model’s applicability to Islamic tourism planning. The refined MOPA framework provides policymakers with a quantitatively validated and ethically grounded decision-support tool for sustainable Sharia tourism development and lays the foundation for future integration with Goal Programming and Simplex optimization.
 
Keywords—multi-criteria decision analysis, Multi-Objective Preference Analysis (MOPA), min–max normalization, Islamic tourism, optimization


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