DocumentCode
3762643
Title
Department recommendations for prospective students Vocational High School of information technology with Na?ve Bayes method
Author
Dyna Marisa Khairina;Fajar Ramadhani;Septya Maharani;Heliza Rahmania Hatta
Author_Institution
Computer Science, Faculty of Mathematics and Natural Science, Mulawarman University, Samarinda, Indonesia
fYear
2015
Firstpage
92
Lastpage
96
Abstract
The selection of the appropriate department in Vocational High School gives the big difference of the ability in thinking for the students. Most students tend to follow their friends in choosing the departments so that the students are possible to feel incompatible with the departments followed and then fail. A student needs to find the department that is suitable to the interest, ability and talent of the student. Each student has the ability to think differently and different talents as well. Naïve Bayes methods are used as decision support to provide recommendations for consideration in the selection of departments appropriately in accordance with the interests, abilities, and talents tendency of students by using reference data to make decisions. Naïve Bayes is a classification with a method of probability and statistics. Bayes´ approach in classification is to find the highest probability with attributes input. All data are entered for calculating the percentage probability in accordance with the criteria in order to obtain the recommendation of appropriate department for prospective students. The criteria used is 4 (four) criteria. The result obtained from the research is the department election system to give the suitable recommendations for the prospective students in considering to decision making.
Keywords
"Multimedia communication","Decision support systems","Bayes methods","Information technology","Computers"
Publisher
ieee
Conference_Titel
Information Technology, Computer, and Electrical Engineering (ICITACEE), 2015 2nd International Conference on
Print_ISBN
978-1-4799-9861-6
Type
conf
DOI
10.1109/ICITACEE.2015.7437777
Filename
7437777
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