Perbandingan Metode MAUT dan Profile Matching Terhadap Sistem Pendukung Keputusan Seleksi Calon Paskibraka - Rizthy Shavna Azizah; Wafiah Murniati; Mardi Mardi (Bulletin of Computer Science Research, 2025)
The selection of candidates for the Flag Raising Troop (Paskibraka) requires an objective, transparent, and consistent assessment system based on physical criteria, general intelligence, personality, marching skills, and physical fitness. This study compares the Multi Attribute Utility Theory (MAUT) and Profile Matching (PM) methods in supporting selection decision making. The MAUT method produces a utility score by considering the weight of each criterion, while PM assesses the level of conformity to the ideal profile through GAP analysis grouped into Core Factor (CF) and Secondary Factor (SF). The purpose of this study is to compare the accuracy of the MAUT and Profile Matching methods in the decision support system for Paskibraka candidate selection. The calculation results show that candidate A3 obtained the highest score in both methods (MAUT = 0.970; PM = 3.600), followed by A1 (MAUT = 0.957; PM = 3.500) and A9 (MAUT = 0.918; PM = 3.450). This consistency indicates a convergence in the assessment of high-performing candidates. However, differences emerge in the middle ranks, for example, A2, which ranked 8th on the MAUT (0.856) but rose to 4th on the PM (3.100). Differences in assessment principles are the main factor: MAUT emphasizes an even distribution of scores across all criteria, while PM focuses more on fit with the ideal profile, particularly on the core criteria (CF). This finding emphasizes that the choice of methods should be tailored to selection priorities, or used in combination to obtain more accurate and objective results.