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Title: | Intelligent Decision Support Systems of Medicinal Forest Plants for Skin Disease |
Other Titles: | 2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT) |
Authors: | Budiman, Edy Wati, Masna Hairah, Ummul Alameka, Faza Jamil, Muh Noorhasanah, Noorhasanah |
Keywords: | forest medicinal-plants skin-disease AHP-WASPAS Borneo |
Issue Date: | 9-Apr-2021 |
Publisher: | IEEE |
Citation: | E. Budiman, M. Wati, Noorhasanah, U. Hairah, F. Alameka and M. Jamil, "Intelligent Decision Support Systems of Medicinal Forest Plants for Skin Disease," 2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT), 2021, pp. 354-359, doi: 10.1109/EIConCIT50028.2021.9431857. |
Series/Report no.: | INSPEC Accession Number;20613522 DOI;10.1109/EIConCIT50028.2021.9431857 |
Abstract: | The richness of Borneo's biodiversity with the potential for indigenous tribal knowledge, one of which is through the use of various types of medicinal plants used in traditional local ethnic medicine, especially those around forest areas. This study aims to develop Borneo's medicinal forest plants decision-making system for skin diseases based on the International Classification of Diseases (ICD-10 version 2016). The determination of medicinal plants for the treatment of skin diseases is based on criteria types of plant species, how to process, how to use, and plant parts used. This research resulted in a decision support system intelligence software product for determining of 94 dataset medicinal forest plants for skin diseases using the AHP method for weight determination (priority), and WASPAS for preference. The implementation of the AHP-WASPAS method in case studies of medicinal forest plants decisions shows that the user's subjectivity in weighting and decision-making criteria affects the recommended preference values. Furthermore, the multi-criteria analysis method approach to decision making in applied case studies is less objective because the knowledge base of alternatives and criteria is complex |
URI: | http://repository.unmul.ac.id/handle/123456789/6707 |
ISBN: | 978-1-6654-0514-0 |
Appears in Collections: | P - Computer Sciences and Information Technology |
Files in This Item:
File | Description | Size | Format | |
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01 - Intelligent Decision Support Systems of Medicinal Forest Plants for Skin Disease.pdf | 574.94 kB | Adobe PDF | View/Open | |
Intelligent_Decision_Support_Systems_of_Medicinal_.pdf | Turnitin | 2.29 MB | Adobe PDF | View/Open |
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