Perbandingan Metode MADM dalam Memilih Pegawai Terbaik dengan Pembobotan Objektif - Andre Hasudungan Lubis; Juanda Hakim Lubis; Dinda Rizky Aprillya (Universitas Budi Darma, 2023)
Nowadays, MADM or Multi-Attribute Decision Making as the part of decision-making theory has been used in various studies to examine decision making problems. Several methods such as SAW, ARAS, and MABAC are the most popular method to be selected to solve these decision-making problems, especially for personnel selection in a company or institute. However, these methods will certainly present various results. Hence, it is necessary to perform a comparison of the most optimal ranking results between these methods. The study focused on comparing those three methods in handling the personnel selection problem through the objective weighting by using SWARA method. The RSI method also employed to ensure the proper method to be used to solve the MADM problem. Five attributes are selected as the references to select best personnel among 38 of them, including Attendance, Discipline, Performance, Punishment, and Achievement. The study reveals that all of the three methods have the identical of RSI score. The results showed that the three methods had almost the same RSI values. The SAW method has the highest RSI value compared to other methods, namely 0.999489; the MABAC method has an RSI value of 0.999416, and the ARAS method with the lowest RSI value, namely 0.999052. Theoretical and practical implications are presented and discussed, along with suggestions for future research.