I. G. P. Asto Buditjahjanto, Andrian Pratama, Muchlas Samani
The performance of a higher education institution is determined by the performance of the lecturers. Lecturer performance is influenced by variables such as motivation, organizational culture, leadership, and continuous professional Development. Meanwhile, the level of lecturer performance is formed from variables such as education and teaching, research, community service, and lecturer support duties. This research aims to develop an intelligent decision system using a hybrid decision tree that is capable of determining the level of lecturers' performance in higher education. The research method used to form an intelligent decision system was formed in three stages. The first stage is to determine the levels of the number of lecturer performances using the elbow method, the second stage is to cluster the level of lecturer performance using the K-means method and the third stage is to determine the level of lecturer performance using the decision tree method. The research results obtained three levels of lecturer performance criteria namely Good, Sufficient, and Poor. The Intelligent Decision System that was built is capable of providing decisions with an accuracy level of 0.889 and a precision level of 0.888. The results obtained are significant enough to be used to determine the level of lecturer performance. © Al-Zaytoonah University of Jordan (ZUJ).
Electrical Engineering, Universitas Negeri Surabaya, Indonesia; Universitas Negeri Surabaya, Indonesia
