Uncertainty Ontology for Module Rules Formation Waterwheel Control

Implementation of Uncertainty model has not given maximum result in forming rule on an inference of a case. For testing to determine whether water quality is high, medium and low. The input variables used are temperature, pH, salinity and Disolved Oxygen. Testing is done by looking at the water turb...

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Main Authors: Zulfian - Azmi, Mahyuddin K. M. Nasution, Herman Mawengkang, M Zarlis
Format: Article
Language:English
Published: Jurusan Ilmu Komputer Universitas Negeri Semarang 2018-05-01
Series:Scientific Journal of Informatics
Subjects:
Online Access:https://journal.unnes.ac.id/nju/index.php/sji/article/view/14188
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spelling doaj-96af0f1e5aca4375b004775ce07804152020-11-25T03:47:51ZengJurusan Ilmu Komputer Universitas Negeri SemarangScientific Journal of Informatics2407-76582018-05-015110.15294/sji.v5i1.141887442Uncertainty Ontology for Module Rules Formation Waterwheel ControlZulfian - Azmi0Mahyuddin K. M. Nasution1Herman Mawengkang2M Zarlis3STMIK Triguna DharmaUniversitas Sumatera Utara, Padang Bulan USU Medan, IndonesiaUniversitas Sumatera Utara, Padang Bulan USU Medan, IndonesiaUniversitas Sumatera Utara, Padang Bulan USU Medan, IndonesiaImplementation of Uncertainty model has not given maximum result in forming rule on an inference of a case. For testing to determine whether water quality is high, medium and low. The input variables used are temperature, pH, salinity and Disolved Oxygen. Testing is done by looking at the water turbidity change in the shrimp pond, to determine the water quality. Its water quality determines in the control module of the waterwheel rotation.Rolling the waterwheel moves quickly if pond water quality is low, moving slowly if water quality is medium and immobile if water quality is good. And the establishment of the rule with the approach of knowledge of Ontology to determine the relation between several variables (temperature, Ph, Disolved Oxygen and salinity). Each variable is set to its certainty value in the form of fuzzy value. Next is determined the relation of the four variables for the formation of rule.https://journal.unnes.ac.id/nju/index.php/sji/article/view/14188neuron, ontology, uncertainty, waterwheel.
collection DOAJ
language English
format Article
sources DOAJ
author Zulfian - Azmi
Mahyuddin K. M. Nasution
Herman Mawengkang
M Zarlis
spellingShingle Zulfian - Azmi
Mahyuddin K. M. Nasution
Herman Mawengkang
M Zarlis
Uncertainty Ontology for Module Rules Formation Waterwheel Control
Scientific Journal of Informatics
neuron, ontology, uncertainty, waterwheel.
author_facet Zulfian - Azmi
Mahyuddin K. M. Nasution
Herman Mawengkang
M Zarlis
author_sort Zulfian - Azmi
title Uncertainty Ontology for Module Rules Formation Waterwheel Control
title_short Uncertainty Ontology for Module Rules Formation Waterwheel Control
title_full Uncertainty Ontology for Module Rules Formation Waterwheel Control
title_fullStr Uncertainty Ontology for Module Rules Formation Waterwheel Control
title_full_unstemmed Uncertainty Ontology for Module Rules Formation Waterwheel Control
title_sort uncertainty ontology for module rules formation waterwheel control
publisher Jurusan Ilmu Komputer Universitas Negeri Semarang
series Scientific Journal of Informatics
issn 2407-7658
publishDate 2018-05-01
description Implementation of Uncertainty model has not given maximum result in forming rule on an inference of a case. For testing to determine whether water quality is high, medium and low. The input variables used are temperature, pH, salinity and Disolved Oxygen. Testing is done by looking at the water turbidity change in the shrimp pond, to determine the water quality. Its water quality determines in the control module of the waterwheel rotation.Rolling the waterwheel moves quickly if pond water quality is low, moving slowly if water quality is medium and immobile if water quality is good. And the establishment of the rule with the approach of knowledge of Ontology to determine the relation between several variables (temperature, Ph, Disolved Oxygen and salinity). Each variable is set to its certainty value in the form of fuzzy value. Next is determined the relation of the four variables for the formation of rule.
topic neuron, ontology, uncertainty, waterwheel.
url https://journal.unnes.ac.id/nju/index.php/sji/article/view/14188
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AT mahyuddinkmnasution uncertaintyontologyformodulerulesformationwaterwheelcontrol
AT hermanmawengkang uncertaintyontologyformodulerulesformationwaterwheelcontrol
AT mzarlis uncertaintyontologyformodulerulesformationwaterwheelcontrol
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