Dosen merupakan pendidik profesional dan ilmuwan yang mempunyai tugas utama untuk mengembangkan, mentransformasikan, dan menyebarluaskan berbagai ilmu pengetahuan melalui pendidikan, penelitian, dan pengabdian kepada masyarakat. Universitas Pohuwato adalah Perguruan Tinggi Swasta baru yang terdapat di Pohuwato yang selalu berupaya dalam meningkatkan Mutu Internal secara berkelanjutan agar dapat bersaing dengan perguruan tinggi lain. Salah satu upaya yang dapat dilakukan adalah melakukan evaluasi terhadap Kinerja Dosen. Maka solusi yang dapat membantu dalam menyelesaikan penilaian kinerja dosen yaitu dibuatlah sebuah sistem pendukung keputusan menggunakan Metode Multy Attribute Utility Theory (MAUT), Metode ini memberikan penilaian hasil akhir dengan melakukan perengkingan dari Nilai Alternatif tertinggi ke terendah. Sistem ini sudah melalui pengujian sistem untuk menghindari kesalahan sistem pengujian White Box dan pengujian Black Box. Berdasarkan hasil pengujian white box disimpulkan bahwa sistem pndukung keputusan ini bebas dari kesalahan program dengan total Cyclomatic Complexity = 7, Region =6, dan independent Path = 7.

Abstrak - Kegiatan pelaksanaan penilaian desa terbaik harus dilakukan dengan terbuka dan kompetitif meskipun jumlah data yang dimasukan relatif banyak. Penilaian desa terbaik sering terkendala, karena setiap desa memiliki karakteristik yang berbeda sehingga menyebabkan nilai kriteria pada masing-masing desa berbeda. Perhitungan dari penilaian masih dilakukan dalam manual sehingga masih banyaknya kesalahan pelaksanaannya dan penilaian desa yang terbaik belum dilaksanakan secara terbuka dan transfaran. Berdasarkan permasalahan tersebut dibutuhkan sistem pendukung keputusan penilaian desa terbaik menggunakan metode Composite Performance Index (CPI) yag dapat diterapkan pada Kecamatan Patilanggio dalam pengambilan keputusan, sehingga dapat diimplementasikan. Sistem pendukung keputusan penilaian desa terbaik hasil dari perhitungan Metode Composite Performance Index (CPI) merupakan prioritas yang dibutuhkan sebagai bahan pertimbangan pada Kecamatan Patilanggio untuk menentukan Penilaian Desa Terbaik. Hasil yang diperoleh SPK Penilaian Desa Terbaik Berdasarkan Hasil Pengujian White Box Disimpulkan Bahwa Sistem Pendukung Keputusan Ini Bebas Dari Kesalahan Program Dengan Total Node(N)= 15, Edge(E)= 18, Predicate Node(P)= 7 Region(R)= 8Kata kunci: SPK, CPI, Penilaian, Desa Terbaik, Patilanggio Abstrack - The activity of implementing the best village assessment must be carried out openly and competitively even though the amount of data entered is relatively large. The assessment of the best village is often constrained, because each village has different characteristics, causing the criteria values for each village to be different. The calculation of the assessment is still done manually so there are still many implementation errors and the best village assessment has not been carried out openly and transparently. Based on these problems, a decision support system for the best village assessment is needed using the Composite Performance Index (CPI) method which can be applied to Patilanggio District in decision making, so that it can be implemented. The decision support system for the best village assessment resulting from the calculation of the Composite Performance Index (CPI) Method is a priority needed as material for consideration in Patilanggio District to determine the Best Village Assessment. The results obtained by the SPK for the Best Village Assessment Based on the White Box Test Results It was concluded that this Decision Support System was free from program errors with Total Node(N)= 15, Edge(E)= 18, Predicate Node(P)= 7 Region(R)= 8Keywords: SPK, CPI, Evaluation, Best Village, Patilanggio

The great spread of the virus, marked by the increasing number of cases and deaths, has led to calls for stay at home, work from home, and distance learning during the pandemic [1]. Therefore, to continue to support distance learning, the government is deemed necessary to ensure the availability of internet data packages for educators and students for the smooth teaching and learning process. Internet data quota assistance is distributed to students, educators, and lecturers [2]. The purpose of this study is to measure the level of user satisfaction through predictions of satisfaction to assist the government in advancing education. At Pohuwato University, the number of valid and eligible recipients of internet assistance reached 578 people, and the number of lecturers was 45. The problem is that many recipients of internet data quota assistance cannot directly convey the impression they feel when using and enjoying the internet quota provided by the government. Meanwhile, the government needs to know the level of user satisfaction to continue striving to improve and advance education. Therefore, a method is needed to help predict the satisfaction of recipients of internet data quota assistance to overcome these problems. Several studies on predicting satisfaction have been widely studied [3][4][5][6]. Still, it was found that the objects, methods, data, and parameters used by several researchers were different, resulting in different predictive values and accuracy. One method often used in prediction is Neural Network with Backpropagation algorithm. This study applies the BP algorithm and PSO feature selection. The results concluded that it successfully predicts visitor satisfaction with an accuracy value of 85.00% [7]. MethodThis study discusses the prediction of satisfaction of recipients of free quota assistance from the Ministry of Education and Culture using the Neural Network with the selection of the Particle Swarm Optimization (PSO) feature.