Implementasi K-Means Clustering Dalam Analisa Soal Ujian CBT Universitas Baiturrahmah - Rico Anggara; Sarjon Defit; Billy Hendrik (LPPM STIKOM Tunas Bangsa, 2024)
Computer-based exams (CBT) are a type of exam where participants take the exam using a computer or digital device. CBT has become a common choice in exam administration. Exam question management is important for CBT success. Participants answer digital questions via a computer interface, and the results are processed automatically by the computer system. The results of this test can be used to assess student understanding and as a learning evaluation. This research aims to group exam questions based on participants' answers. The method used in this research is K-Means Clustering. This method has 5 stages, namely cluster center initialization, data grouping, calculation of new cluster centers, convergence and evaluation of results. This process repeats until the cluster center does not change any more or convergence has been achieved. Next, the K-Means Clustering algorithm is applied to group exam questions into appropriate clusters. This grouping process is carried out by considering the similarities between the exam questions based on the number of correct answers and the number of incorrect answers. Dataset source from UPT CBT, Baiturrahmah University. The question dataset consists of 100 exam questions that have been tested on students at the Faculty of Medicine, Baiturrahmah University. The results of this research can group exam questions into groups of difficult questions, medium questions and easy questions. This research can be a reference for academics in evaluating exam questions created by lecturers and can evaluate the level of understanding of students at Baiturrahmah University.