<![CDATA[Abstract: The selection of exemplary Government Employees Non-Civil Servants (PPNPN) is a strategic initiative aimed at fostering a productive, disciplined, and professional work culture within government institutions. This system is designed to assist the evaluation and selection process of outstanding PPNPN at Ahmad Yani Meteorological Station, replacing conventional assessment methods that previously focused mainly on attendance and communication, which were often considered subjective and time-consuming. The evaluation involved 10 PPNPN assessed based on eight key criteria: productivity, personality and loyalty, attendance, job responsibility, initiative, honesty, neatness, and teamwork. Data were collected through questionnaires distributed to Civil Servants (ASN) at Ahmad Yani Meteorological Station, who are directly involved in the daily performance assessment of the PPNPN. The results show that the Simple Additive Weighting (SAW) method effectively ranked PPNPN performance, with the highest score of 100 achieved by MH and the lowest score of 95.2 by HS. The implementation of the SAW method is expected to provide transparent, objective, and measurable results to support data-driven decision-making in employee performance evaluations. Keyword: Decision Support System; SAW; PPNPN; Performance Evaluation Abstrak: Pemilihan Pegawai Pemerintah Non Pegawai Negeri (PPNPN) teladan merupakan langkah strategis dalam mendorong budaya kerja yang produktif, disiplin, dan profesional di lingkungan instansi pemerintahan. Sistem ini dirancang untuk menjadi alat bantu dalam proses evaluasi dan seleksi PPNPN teladan di Stasiun Meteorologi Ahmad Yani, menggantikan metode penilaian konvensional yang sebelumnya hanya berpusat pada presensi dan komunikasi yang dinilai kurang objektif dan memakan waktu. Prosesevaluasi melibatkan 10 orang PPNPN yang dinilai berdasarkan delapan kriteria utama, yakni produktivitas, perilaku kepribadian dan loyalitas, kehadiran, tanggung jawab pekerjaan, inisiatif, kejujuran, kerapihan, dan kerjasama. Data dikumpulkan melalui penyebaran kuesioner kepada Aparatur Sipil Negara (ASN) di Stasiun Meteorologi Ahmad Yani sebagai responden yang terlibat langsung dalam penilaian kinerja harian para PPNPN. Hasil penelitian menunjukan bahwa metode SAW berhasil menyusun peringkat kinerja PPNPN secara efektif. Dimana didapat nilai tertinggi yaitu 100 atas nama MH dan nilai terendah yaitu HS dengan nilai 95.2. Dengan metode SAW ini diharapkan mampu memberikan hasil yang transparan, objektif, dan terukur dalam mendukung proses pengambilan keputusan berbasis data dalam evaluasi kinerja pegawai. Kata kunci: Sistem Pendukung Keputusan; Simple Additive Weighting; PPNPN; Penilaian Kinerja]]>
