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Submitted
May 19, 2024
Accepted
June 8, 2024
Published
June 10, 2024
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Abstract

Kalimantan has extraordinary biodiversity, including medicinal plants. Medicinal plants are a type of plant that certain parts, such as roots, leaves, bark, stems, and the results of their excretions. However, people sometimes need help choosing plants that suit their needs because of the many types of medicinal plants and the need for knowledge regarding their use. Decision support systems (DSS) combine computer capabilities with data processing or manipulation that utilizes unstructured models or solution rules. Furthermore, the method of documenting knowledge of traditional medicine is through the media of information systems. This system helps select medicinal plants according to user needs. This research developed a DSS using Rank Order Centroid (ROC) and Multi-Objective Optimization by Ratio Analysis (MOORA) methods to select medicinal plants for fungal and skin infections, including Furuncles, Tinea corporis, Tinea versicolor, and Acne. ROC method for determining criteria weight values. This research has four criteria: plant part, processing method, use method, and habitus. Determining recommendations for alternative ranking results using the MOORA method. This study aims to help the public get recommendations for medicinal plants in human skin disease treatment. This study aims to increase the preservation of biodiversity, particularly sustainable medicinal plants in the tropical rainforest of East Kalimantan.

Keywords

Decision Support System, Information system, Medicinal plants, MOORA, ROC

Article Details

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Copyright (c) 2024 TEPIAN

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Author Biography

Andi Tejawati, Informatics, Engineering, Mulawarman University

Department of Informatics

How to Cite
Widians, J. A., Tejawati, A., & Yuniarti, W. D. (2024). Medicinal Plants Recommendation System using ROC and MOORA. TEPIAN, 5(2), 87–92. https://doi.org/10.51967/tepian.v5i2.3019
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