Decision Support System Design for Determining Exemplary Lecturer using Simple Additive Weighting (SAW)

Abstract

STMIK AKAKOM has 67 lecturers. In each semester, an evaluation is held to determine lecturers’ performance to maintain good institutional quality. The evaluation process is based on students’ and Department Quality-Assurance Team (DQAT) assessments. Up until now, the results of these evaluations were left unprocessed. This study aimed to determine well-performed and less-performed lecturers by combining evaluation results from students and DQAT using the simple additive weighting (SAW) method. There are 17 criteria used in this study with different weight values. The results showed that the technique determined the lecturers’ ranking significantly based on their respective performance. The most well-performed lecturer is L40 with Vi (order for lecturer) value of 0.95, the second is L41 with Vi value of 0.92, and the third one is L25 with Vi of 0.91, while the most under-performed lecturer is L67 with a Vi value of 0.72.