Penilaian kinerja tenaga pendidik dan kependidikan merupakan salah satu faktor penting dalam meningkatkan kualitas pendidikan di sekolah. Namun, proses penilaian yang masih menggunakan instrumen kertas dan pengolahan data Microsoft Excel sering menimbulkan masalah seperti ketidakakuratan dan membutuhkan waktu yang lama. Selain itu, data hasil penilaian belum tersimpan secara terpusat sehingga menyulitkan proses evaluasi dan pelaporan. Untuk mengatasi permasalahan tersebut, diterapkan sistem pendukung keputusan menggunakan metode Multi Attribute Utility Theory (MAUT) agar proses penilaian menjadi lebih akurat. Penelitian ini menggunakan 43 data alternatif dengan kriteria tanggung jawab, kepatuhan, etika kerja, kerja sama, dan absensi. Tujuan penelitian ini agar mempermudah pihak sekolah dalam melakukan penilaian kinerja tenaga pendidik dan kependidikan. Hasil penelitian berupa nilai preferensi akhir dan peringkat berdasarkan metode Multi Attribute Utility Theory (MAUT). Hasil perhitungan menunjukkan bahwa alternatif A16 memperoleh nilai preferensi tertinggi sebesar 0.86226, sedangkan alternatif A6 memperoleh nilai preferensi terendah sebesar 0.03654. Sistem yang dibuat dapat membantu proses pengambilan keputusan secara lebih efektif dan efisien.

The performance evaluation of teaching and non-teaching staff is a key factor in improving the quality of education in schools. However, evaluation processes that still rely on paper-based instruments and data processing in Microsoft Excel often lead to problems such as inaccuracies and time-consuming procedures. Additionally, evaluation results are not stored centrally, which complicates the evaluation and reporting processes. To address these issues, a decision support system using the Multi-Attribute Utility Theory (MAUT) method was implemented to make the evaluation process more accurate. This study utilized 43 alternative data points based on the criteria of responsibility, compliance, work ethics, cooperation, and attendance. The objective of this study is to facilitate schools in conducting performance evaluations of teaching and non-teaching staff. The research results consist of final preference scores and rankings based on the Multi-Attribute Utility Theory (MAUT) method. The calculation results show that alternative A16 obtained the highest preference score of 0.86226, while alternative A6 obtained the lowest preference score of 0.03654. The developed system can assist in the decision-making process more effectively and efficiently.