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dc.contributor.authorKhairina, Dyna Marisa
dc.contributor.authorFajar, Ramadhani
dc.contributor.authorMaharani, Septya
dc.contributor.authorHatta, Heliza Rahmania
dc.date.accessioned2020-07-02T03:36:54Z
dc.date.available2020-07-02T03:36:54Z
dc.date.issued2016
dc.identifier.isbn978-1-4799-9863-0
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/4673
dc.description.abstractThe 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. Naive 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.en_US
dc.language.isoenen_US
dc.publisherIEEE / Universitas Diponegoroen_US
dc.relation.ispartofseriesInternational Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE);
dc.subjectdecision making; naïve bayes; vocational high schoolen_US
dc.titleDepartment Recommendations for Prospective Students Vocational High School of Information Technology with Naïve Bayes Methoden_US
dc.typeArticleen_US


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