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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Jurusan Ilmu Komputer Universitas Negeri Semarang
2018-05-01
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Online Access: | https://journal.unnes.ac.id/nju/index.php/sji/article/view/14188 |
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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 |
work_keys_str_mv |
AT zulfianazmi uncertaintyontologyformodulerulesformationwaterwheelcontrol AT mahyuddinkmnasution uncertaintyontologyformodulerulesformationwaterwheelcontrol AT hermanmawengkang uncertaintyontologyformodulerulesformationwaterwheelcontrol AT mzarlis uncertaintyontologyformodulerulesformationwaterwheelcontrol |
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