Selecting Palm Oil Cultivation Land using ARAS Method

2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2019-12-01 DOI:10.1109/ISRITI48646.2019.9034593

Muhammad Ari Prayogo, Jatmiko Endro Suseno, Dinar Mutiara Kusumo Nugraheni

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引用次数: 2

Abstract

The importance of selecting alternative land used for palm oil cultivation requires some priority assessment of the land, therefore the need to implement a decision support system in choosing which land to plant palm oil in the future. There is no system for selecting land priority to plant palm oil purpose of this study is to develop a system for selecting palm oil cultivation land by implementing a decision support system using the Additive Ratio Assessment (ARAS) method in analyzing each alternative land criteria. The results showed that the alternative lands ranking that had the highest value AL3, which was Mendik Makmur, had the highest K value of 0.869, which placed the land Mendik Makmur in the first rank based on ARAS method calculations. The resulting accuracy testing ARAS method by comparing the ranking results with other methods against the results of expert assessments get an accuracy score of 77%, with 7 alternative ranking positions are the same as the results of the assessment of experts from a total of 9 alternatives.

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利用ARAS法选择棕榈油种植用地

选择用于棕榈油种植的替代土地的重要性要求对土地进行一些优先评估，因此需要在未来选择种植棕榈油的土地时实施决策支持系统。目前尚无选择土地优先种植棕榈油的系统，本研究的目的是通过在分析每个备选土地标准时使用加性比率评估(ARAS)方法实施决策支持系统，开发棕榈油种植土地选择系统。结果表明:AL3值最高的备选土地排名为门迪克·Makmur, K值最高，为0.869，根据ARAS方法计算，门迪克·Makmur土地居首位;所得到的准确性测试ARAS方法通过将排名结果与其他方法的专家评估结果进行比较，得到准确率分数为77%，其中7个备选排名位置与9个备选专家的评估结果相同。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

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