Implementation of Weighted Naive Bayes Algorithm for Major Determination in Indonesian High School

Major selection for 9
^th
grade students aim to focus the student on building the skill and passion that they owned. It is also aimed to build the students' potential, passion and talent. By selecting the major that students passionate about, it is expected that they can improve the score of academic students. The process of major selection today has many drawbacks. One of them is that the process only considering the preference of students without looking at the students' academic background. This resulted in possible problem for students in the future, for example the students will not be able to pass the grades. In addition, the major selection will also affect the possible course when the students decide to continue their study to university level. This study proposed major selection by applying the techniques of classification in data mining. Weighted Naive Bayes Algorithm is implemented to determine high school major of students in junior high school of 33 Semarang. Experimental result shows 80% in accuracy. The system prototyping is developed for the visualization that can help student to determine major in senior high school.