Evaluation of Decision Support System Models in Tourism Ambassador Selection

<p><em>Tourism Ambassador selection still faces issues of subjectivity in assessment, highlighting the need for an objective system to evaluate various aspects of participant competence. This study aimed to assess the performance of seven Decision Support System methods—SAW, WP, TOPSIS, MOORA, MAUT, PROMETHEE, and SMART—in a selection process based on four criteria: Public Speaking, Tourism Knowledge, English Proficiency, and Talent. Data from 12 participants were analyzed and evaluated using classification accuracy, Mean Absolute Error, Root Mean Square Error, and Spearman and Kendall rank correlations against the actual ranking. The results showed that PROMETHEE delivered the best performance, achieving 100% accuracy with perfect ranking alignment. These findings indicate that PROMETHEE is highly suitable for multi-criteria selection processes requiring high precision in determining result order.</em><em></em></p><p><strong><em>K</em></strong><strong><em>eywords</em></strong><strong><em>:</em></strong><em> Decision Support System; PROMETHEE method; Multi-criteria selection; Method evaluation; Tourism Ambassador</em><em></em></p><p align="center"> </p><p align="center"><strong>Abstrak</strong></p><p>Pemilihan Duta Pariwisata masih menghadapi persoalan subjektivitas dalam penilaian, sehingga diperlukan sistem yang lebih objektif untuk menilai berbagai aspek kompetensi peserta. Penelitian ini bertujuan mengevaluasi kinerja tujuh metode Sistem Pendukung Keputusan, yaitu <em>SAW, WP, TOPSIS, MOORA, MAUT, PROMETHEE</em> dan <em>SMART</em>, dalam proses seleksi berbasis empat kriteria: <em>Public Speaking</em>, Kepariwisataan, Bahasa Inggris, dan Bakat. Data dari 12 peserta dianalisis dan dievaluasi menggunakan metrik akurasi klasifikasi, <em>Mean Absolute Error, Root Mean Square Error</em>, serta korelasi Spearman dan Kendall terhadap ranking asli. Hasil menunjukkan bahwa <em>PROMETHEE</em> memberikan performa terbaik dengan akurasi 100% dan kesesuaian ranking yang sempurna. Temuan ini menunjukkan bahwa PROMETHEE sangat tepat diterapkan dalam proses seleksi multi-kriteria yang memerlukan ketelitian tinggi dalam penentuan urutan hasil.</p><p> </p>