ESTIMATED GRADUATION OF GRAPHIC DESIGN TRAINEES AT LPK2-PASCOM IN TAKING COMPETENCY EXAMS WITH THE SUPPORT VECTOR MACHINE (SVM) ALGORITHM - Ndruru, Eferoni; Zebua, Taronisokhi (Sean Institute, 2022)
This paper aims to predict the graduation of graphic design training participants at computer course training institutions to take competency exams by applying the Support Vector Machine (SVM) algorithm. Data sourced through field studies and literature studies. Among them by conducting direct observations and interviews on research objects and supported by the appropriate literature. While the data analysis method used is descriptive qualitative method. From the results of the research that the researchers have done, there are obstacles, including: many participants did not pass, because they were not sure enough to select their abilities during the training whether they deserved to be tested or not. Therefore, the author intends to create a graduation estimation system using the Support Vector Machine (SVM) algorithm. So it is hoped that this system can predict the passing of competency test participants.