Expert System Based on an Ontology Method to Analyze Types of Arabica Coffee Beans

Authors

DOI:

https://doi.org/10.3991/ijes.v5i2.6908

Abstract


In the past few decades, the use of ontologies in information systems has become popular in many fields, such as website development, database integration, and natural language processing. Because many kinds of coffee beans can be used in coffee shops, the prospective coffee house entrepreneur meets obstacles in terms of choosing the right coffee beans because of multiple unique characteristics. In order to help this cohort make decisions, our study proposed a simulation ontology-based matching for coffee bean selection by inserting three parameters—aroma, flavor, and sour level—as inputs on the website. Arabica coffee bean is used as the principal object in this study and the outputs would be the beans matched with the parameters that had been inserted. In this study, the system model gained from the ontology method is shown in the implementation by using an example.

Key Words—Arabica coffee beans, Ontology, OWL, Protégé, SPARQL

Author Biographies

Michelle Angelica, Universitas Multimedia Nusantara

Student at Universitas Multimedia Nusantara. Young technopreneur with high passion in programing and business development. Have experienced with programing language like php and java.

Friska Natalia Ferdinand, Universitas Multimedia Nusantara

Friska Natalia Ferdinand is Head of Research Center in Multimedia Nusantara University also Lecturer in Department of Information Systems. She received her Ph.D. in Industrial Engineering from Kyungsung University, Busan, Republic of Korea. Her teaching and research interests include system and analysis design, logistics, e- business and computer programming. She can be reached by e-mail at friska.natalia@umn.ac.id

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Published

2017-07-06

How to Cite

Angelica, M., & Ferdinand, F. N. (2017). Expert System Based on an Ontology Method to Analyze Types of Arabica Coffee Beans. International Journal of Recent Contributions from Engineering, Science & IT (iJES), 5(2), pp. 31–41. https://doi.org/10.3991/ijes.v5i2.6908

Issue

Vol. 5 No. 2 (2017)

Section

Papers

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