Simple Additive Weight Algorithm to Determine Lecturer Competency in Hybrid Learning Approach
DOI:
https://doi.org/10.30872/jim.v19i1.14158Keywords:
Hybrid Learning, Decision Support System, Simple Additive Weighting,Abstract
As the COVID-19 vaccination process continues, the pandemic is starting to subside. All educational institutes in Indonesia are starting to transition from online learning to hybrid learning. One crucial factor in the learning process is the competency of the lecturers. However, some students still feel dissatisfied with the learning process due to the lack of competence from the lecturers. This is exacerbated by the students and lecturers’ lack of familiarity with the hybrid learning system. Therefore, the aim of this research is to find a fair evaluation model for the lecturer’s competency that is suitable for the current hybrid learning approach. The data used in this research comes from questionnaires filled out by all students of Dian Nuswantoro University every year before the Final Semester Exam (UAS). The questionnaire consists of 10 questions regarding the hybrid learning process in the academic year of 2022/2023. Students provide their answers using a 4-point Likert scale, consisting of "Strongly Agree," "Agree," "Disagree," and "Strongly Disagree." The responses from students are grouped based on the courses/classes taught by the lecturers. The evaluation of lecturers’ competency is represented by two aspects: knowledge mastery and teaching skill. Each aspect of the lecturers’ evaluation consists of 5 questions in the questionnaire. The method used to evaluate the lecturers’ competency is the Decision Support System (DSS) algorithm combined with Simple Additive Weight (SAW). Result shows that students are mostly pleased with the quality of the lectures presented. Furthermore, lecturers with high evaluation scores tend to have a small number of students.
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