<![CDATA[The process of selecting the best employees in government institutions is often conducted manually, which can lead to subjectivity and inconsistent outcomes. This study aimed to improve the objectivity and efficiency of the evaluation process by applying the Multi-Criteria Decision Making (MCDM) approach. Four methods, namely SMART, MOORA, WASPAS, and PROMETHEE, were used to compare ranking results based on eight employee performance criteria. The findings revealed that the top three employees consistently occupied the same positions across all methods, with a Kendall’s W coefficient of 0.9949 (p < 0.001), indicating an almost perfect level of agreement. The Friedman and Wilcoxon tests also confirmed no significant differences among ranking results. Based on performance and flexibility, the PROMETHEE method is recommended as the most adaptive approach for preference-based decision systems, while SMART excels in ease of implementation and computational transparency. This study reinforces comparative validation among MCDM methods as a foundation for developing data-driven decision support systems.Kata kunci: Decision Support System; Employee Performance; MCDM; Comparative Analysis; Statistical ValidationAbstrakProses penilaian pegawai terbaik di instansi pemerintah sering kali dilakukan secara manual, sehingga berpotensi menimbulkan subjektivitas dan ketidakkonsistenan hasil. Penelitian ini bertujuan meningkatkan objektivitas dan efisiensi proses penilaian tersebut dengan menerapkan pendekatan Multi-Criteria Decision Making (MCDM). Empat metode, yaitu SMART, MOORA, WASPAS, dan PROMETHEE digunakan untuk membandingkan hasil peringkat berdasarkan delapan kriteria kinerja pegawai. Hasil penelitian menunjukkan bahwa ketiga pegawai terbaik secara konsisten menempati posisi yang sama pada seluruh metode dengan nilai koefisien Kendall’s W sebesar 0,9949 (p < 0,001), yang menunjukkan tingkat kesesuaian hampir sempurna. Analisis Friedman dan Wilcoxon juga menunjukkan tidak terdapat perbedaan signifikan antar hasil peringkat. Berdasarkan kinerja dan fleksibilitasnya, metode PROMETHEE direkomendasikan sebagai pendekatan paling adaptif untuk sistem berbasis preferensi, sedangkan SMART unggul dalam kemudahan implementasi dan transparansi perhitungan. Penelitian ini memperkuat validasi komparatif antar metode MCDM sebagai dasar pengembangan sistem pendukung keputusan berbasis data. ]]>
