Analysis Optimization K-Nearest Neighbor Algorithm with Certainty Factor in Determining Student Career
Nunsina, Tulus Tulus, Zakarias Situmorang · 2020
K-Nearest Neighbour is a method for data classification, similar to a nearby neighbour, while the certainty factor is an uncertain decision-making method. In this study, students’ interest, talent and exam scores were used to determine a career-appropriate decision for each student. The Student career prediction system is done by combining two methods of K-Nearest Neighbour and Certainty Factor. It was expected that the two way analysis could provide better information for students in determining their career. The K-Nearest Neighbour method received a value derived from the Certainty Factor beneficial in predicting career prediction. Data used for this study was the training data and test data of 78 students and 24 students selected through questionnaire. The combination of these two methods resulted accuracy value on K-Nearest Neighbour Value k = 3 was 70%, and the Certainty factor combines at 0.99%. The combination of both the K-Nearest Neighbour and Certainty Factor method obtained 93.83% value.