Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/13300
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dc.contributor.authorAbadi, S.en_US
dc.contributor.authorHawi, A.en_US
dc.contributor.authorAklaen_US
dc.contributor.authorDacholfany, I.en_US
dc.contributor.authorHuda, M.en_US
dc.contributor.authorTeh, K.S.M.en_US
dc.contributor.authorWalidi, J.en_US
dc.contributor.authorHashim, W.en_US
dc.contributor.authorMaseleno, A.en_US
dc.date.accessioned2020-02-03T03:31:40Z-
dc.date.available2020-02-03T03:31:40Z-
dc.date.issued2019-
dc.description.abstractThe process of disease identification of paddy must be in accordance with predetermined criteria. To assist in selecting the determination of participants, they must identify disease characteristics, a decision support system is needed. One method that can be used for decision support systems is FMADM (Fuzzy Multiple Addective Decision Making). Where in this study using the method of SAW (Simple Addictive Weighted) is to find the best alternative from several alternatives. Where the best alternative is based on predetermined criteria. This method was chosen because it was able to choose the best alternative, namely the best identification based on the criteria entered, then look for the weight score of each attribute, after the process of looking for ranking to get the best alternative, namely disease in paddy. © 2019, Advanced Scientific Research. All rights reserved.
dc.language.isoenen_US
dc.titleIdentification of sundep, leafhopper and fungus of paddy by using fuzzy SAW methoden_US
dc.typeArticleen_US
dc.identifier.doi10.31838/ijpr/2019.11.01.093-
item.fulltextNo Fulltext-
item.grantfulltextnone-
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