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dc.contributor.authorGifari, Okta Ihza
dc.contributor.authorAgus, Fahrul
dc.contributor.authorRamadiani, Ramadiani
dc.contributor.authorAzhari, Muhamad
dc.contributor.authorSunyoto, Andi
dc.date.accessioned2022-01-15T09:11:58Z
dc.date.available2022-01-15T09:11:58Z
dc.date.issued2021-10-06
dc.identifier.isbnISBN: 978-1-6654-0807-3
dc.identifier.otherIEEE Catalog Number: CFP21X12-ART
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/10237
dc.description.abstractAbstract— Coelogyne pandurata or better known by Kalimantan Black Orchid. This plant is an epiphytic orchid that is attached to other plants but is not dangerous. This orchid is one of Kalimantan’s endemic plants that require human intervention to save its sustainability. Black Orchid Plants are very susceptible to various pests and diseases; therefore, applications are needed that can provide insight to ornamental plant farmers. This study uses the Naïve Bayes methods in the application of Expert Systems to diagnose pests and diseases of Black Orchid plants. There are 24 types of symptoms and nine types of diagnostic results. The results of this study are expected to provide a solution for cultivating Black Orchid plants so that they can find out the symptoms of pests and plant diseases early on. Nine diagnostic results consist of 4 types of pests and five types of disease. This application has a Mean Absolute Percentage Error (MAPE) value of 2.456%.en_US
dc.language.isoen_USen_US
dc.publisher2021 IEEE 7th Information Technology International Seminar (ITIS) Surabaya, Indonesia, October 6-8, 2021en_US
dc.subjectExpert Systemsen_US
dc.subjectBayes Theorem Methoden_US
dc.subjectBlack Orchiden_US
dc.subjectPests Plant Diseaseen_US
dc.subjectMean Absolute Percentage Error (MAPE)en_US
dc.titleDiagnose Pest and Disease of Black Orchid Plant Using Naive Bayes Methoden_US
dc.typeArticleen_US


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