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Ontology based knowledge modelling for Indonesian rice varieties

Author(s)
SOFI DEFIYANTI Faculty of Computer Science, Universitas Singaperbangsa Karawang, Karawang, Indonesia
AHMAD ASHARI Dept. of Computer Science and Electronics, Universitas Gadjah Mada, Yogyakarta, Indonesia
DANANG LELONO Dept. of Computer Science and Electronics, Universitas Gadjah Mada, Yogyakarta, Indonesia
Abstract
Knowledge is an asset for every organization, including knowledge about new superior varieties of rice developed by the Agricultural Research and Development Agency of the Ministry of Agriculture of the Republic of Indonesia. Until 2021, as many as 120 new superior varieties of rice have been published, but knowledge of the improved varieties developed is only limited. Many varieties cause farmers to be confused in determining the rice varieties to be planted. So that a knowledge model is needed that can formalize knowledge about rice varieties, one way is to develop a rice variety ontology model. We propose the Ontology Varieties Rice (OntVarRice), an ontology of new superior rice varieties in Indonesia, by following the MethOntology methodology, which consists of a specification, conceptualization, formalization, and implementation of the ontology. OntVarRice includes 32 classes, 16 object properties, 7 data properties, 167 individuals, and 2430 logical axioms implemented using OWL. Evaluation and validation using HermiT to test consistency and coherence, and Description Logic query (DL query) is used to verify the knowledge built based on the answers to competency questions. OntVarRice as a knowledgebases model can improve agricultural practices to make optimal decisions because OntVarRice stores and models knowledge about new superior rice varieties in the form of a complete picture of the concept of new superior rice varieties that can maximize variety selection, yield potential, production quality, pest, and disease resistance.
Publication Details
Page(s) 6861-6873
DOI DOI not available
Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 23, Year: 2022

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Keywords
Rice, varieties, Agriculture, Ontology Deployment, Knowledge-Based
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