AN APPLICATION OF ROUGH SET THEORY TO CLUSTER STUDENT ASSESSMENT AT UNIVERSITIES

Abstract

Assessment is the last session of a lecture in college. There are several components that form the basis of calculations. A technique to select a clustering attribute based on rough set theory is presented. Dataset is taken from a survey of 150 architectural design studio students. Data are taken on 6th semester students majoring in architecture University of Technology of Yogyakarta Indonesia. Assessment consists of five components, namely three tasks, presentations, midterms and final exams. This assessment was conducted in 2015. The evaluation criteria used range from 0-100. Student name, age, race, and attendance are not required in this assessment. In this study, we show how to determine the dominant attributes of a set of attributes of an assessment list by using the rough set theory (Max-Max roughness). The results obtained can potentially contribute to give a recommendation in awarding the final grade of a course more quickly and accurately.

Keywords : Assessment, Clustering, Rough set theory, Attributes