Semantic Web Knowledge Base on the Modeling of Study Program Recommendation System
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Abstract
Prospective students have wider choice of opportunities as opposed to many choices of study majors offered by higher education institution. On the other hand, it can also cause difficulties for students to make the right choice. How a student make decision regarding his or her choice of study major is influenced by several factors, including student interest, majors chosen at the previous school level, students’ aspirations, as well as entry requirements at a particular university. This research aims to design a model of an information system that can make it easier for a student to obtain information about the most appropriate study program, among the many study programs offered by the university. The information generated by this system can be used as a reference to support recommendations for prospective students in deciding which study program they will choose appropriately. The system is designed by utilizing semantic web technology, by building an ontology based on several knowledge-bases to represent new knowledge. The ontology model designed in OWL format succeeded in connecting several knowledge-bases into comprehensive and contextual knowledge as a source of information that can be used by a prospective student to choose a study program based on these recommendations. Protege is used for ontology modeling, while implementation on the web server is done using Apache Jena platform.
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[1]
I. Santosa, P. Y. Wiwaha, and B. R. Suteja, “Semantic Web Knowledge Base on the Modeling of Study Program Recommendation System”, JuTISI, vol. 9, no. 2, pp. 200 –, Aug. 2023.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial used, distribution and reproduction in any medium.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.