Ontology Based Knowledge Modelling for Indonesian Rice Varieties
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 publ...
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Format: | Other |
Language: | English |
Published: |
Journal of Theoretical and Applied Information Technology
2022
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Online Access: | https://repository.ugm.ac.id/284280/1/159.%20Ontology.pdf |
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author | Defiyanti, Sofi Ashari, Ahmad Lelono, Danang |
author_facet | Defiyanti, Sofi Ashari, Ahmad Lelono, Danang |
author_sort | Defiyanti, Sofi |
collection | UGM |
description | 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 |
first_indexed | 2024-03-14T00:09:54Z |
format | Other |
id | oai:generic.eprints.org:284280 |
institution | Universiti Gadjah Mada |
language | English |
last_indexed | 2024-03-14T00:09:54Z |
publishDate | 2022 |
publisher | Journal of Theoretical and Applied Information Technology |
record_format | dspace |
spelling | oai:generic.eprints.org:2842802023-12-04T08:49:58Z https://repository.ugm.ac.id/284280/ Ontology Based Knowledge Modelling for Indonesian Rice Varieties Defiyanti, Sofi Ashari, Ahmad Lelono, Danang Electronic and Instrumentation System 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 Journal of Theoretical and Applied Information Technology 2022 Other NonPeerReviewed application/pdf en https://repository.ugm.ac.id/284280/1/159.%20Ontology.pdf Defiyanti, Sofi and Ashari, Ahmad and Lelono, Danang (2022) Ontology Based Knowledge Modelling for Indonesian Rice Varieties. Journal of Theoretical and Applied Information Technology. https://efaidnbmnnnibpcajpcglclefindmkaj/https://www.jatit.org/volumes/Vol100No23/3Vol100No23.pdf |
spellingShingle | Electronic and Instrumentation System Defiyanti, Sofi Ashari, Ahmad Lelono, Danang Ontology Based Knowledge Modelling for Indonesian Rice Varieties |
title | Ontology Based Knowledge Modelling for
Indonesian Rice Varieties |
title_full | Ontology Based Knowledge Modelling for
Indonesian Rice Varieties |
title_fullStr | Ontology Based Knowledge Modelling for
Indonesian Rice Varieties |
title_full_unstemmed | Ontology Based Knowledge Modelling for
Indonesian Rice Varieties |
title_short | Ontology Based Knowledge Modelling for
Indonesian Rice Varieties |
title_sort | ontology based knowledge modelling for indonesian rice varieties |
topic | Electronic and Instrumentation System |
url | https://repository.ugm.ac.id/284280/1/159.%20Ontology.pdf |
work_keys_str_mv | AT defiyantisofi ontologybasedknowledgemodellingforindonesianricevarieties AT ashariahmad ontologybasedknowledgemodellingforindonesianricevarieties AT lelonodanang ontologybasedknowledgemodellingforindonesianricevarieties |