Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/1839
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dc.contributor.authorAgus, Fahrul
dc.contributor.authorIhsan, Muh.
dc.contributor.authorKhairina, Dyna Marisa
dc.contributor.authorCandra, Krishna Purnawan
dc.date.accessioned2019-11-05T15:29:28Z
dc.date.available2019-11-05T15:29:28Z
dc.date.issued2019
dc.identifier.issn2046-1402
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/1839
dc.description.abstractOne of the factors causing rice production disturbance in Indonesia is that farmers lack knowledge of early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make an early diagnosis of rice plant diseases. Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts and uses a Waterfall Paradigm and Unified Modeling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with a sensitivity of 87.5%. ESforRPD2 is available in Indonesian at http://esforrpd2.blog.unmul.ac.id
dc.publisherF1000Research
dc.titleESforRPD2 : Expert System for Rice Plant Disease Diagnosis
Appears in Collections:J - Agriculture

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