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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Main Authors: Defiyanti, Sofi, Ashari, Ahmad, Lelono, Danang
Format: Other
Language:English
Published: Journal of Theoretical and Applied Information Technology 2022
Subjects:
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
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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