Studi Komparasi Algoritma Naïve Bayes Classifier dan Radian Basis Function Network Untuk Pemodelan Tingkat Motivasi Berprestasi Mahasiswa Vokasi
Abstract
Vocational education aims to prepare graduates who are directed to specific field skills in accordance with the business world and industry. The learning environment in vocational education is developed in accordance with the business world and the industrial world so it takes the involvement of students directly in the learning activities. One of the important factors that influence student involvement in learning activities is the factor that comes from within the student itself. Based on the importance of empowerment of achievement motivation in learning vocational education, then the required level of motivation achievement of students before the learning process. This study aims to compare two algorithms namely naïve bayes classifier and radian base function network which will be used to design a system that can model the level of student motivation to achieve. From the test results collected that the use of Radial Function Network gives better accuracy results. However, the researchers note that the difference in the value of the accuracy of both is not too high, only 1.65%, sehigga we conclude the two algorithms can be used as machine learning algorithm, given the speed of time of execution owned by Naïve Bayes Classifier then this algortima is still very worthy to be used as the core of the system to be developed.
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Keywords— vocational student, naïve bayes classifier, radian basis function network, achievement motivation student.
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