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Group Decision Support System to Determine Regional Development Priority Using the Item-Based Clustering Hybrid Method

机译:基于项目的聚类混合方法确定区域发展优先权的群体决策支持系统

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Abstract: Determination of regional development priorities is usually influenced by two factors, firstly the policy-making subjectivity (regional head) second to the results of the development data analysis. But both often do not go hand in hand because in fact subjectivity is more dominant than combining the two. The development of computational technology, especially in the area of decision support, provides space to solve various problems related to the decision making process. This study aims to develop a Group Decision Support System (GDSS) model for determining regional development priorities in the future. An alternative approach in the form of developing a GDSS model is carried out so that it can be used to determine regional development priorities that are able to combine analysis of data on development results and subjectivity of policy makers. It means, policy-enforcing subjectivity still exists but the results of development data analysis are also used. This model combines the GDSS concept, MVHAC cluster technique and Item-based Cluster Hybrid Method (ICHM) to accommodate joint decision making from each group decision maker. The results of the testing of the model developed against six regions in Banten Province show that there are three regions that must be prioritized in the future. Those are Pandeglang, Lebak and Kota Serang.
机译:摘要:确定区域发展重点通常受两个因素影响,首先是决策主观性(区域负责人),其次是发展数据分析的结果。但是两者往往并不能齐头并进,因为实际上主观性比结合两者更为主导。计算技术的发展,尤其是在决策支持领域,为解决与决策过程相关的各种问题提供了空间。这项研究的目的是建立一个团体决策支持系统(GDSS)模型,以确定未来的区域发展重点。采取了开发GDSS模型形式的替代方法,以便可以将其用于确定区域发展优先级,这些优先级能够将对发展成果和政策制定者的主观数据进行分析相结合。这意味着,执行政策的主观性仍然存在,但也使用了发展数据分析的结果。该模型结合了GDSS概念,MVHAC聚类技术和基于项目的聚类混合方法(ICHM),以适应每个小组决策者的联合决策。针对万丹省六个地区开发的模型的测试结果表明,将来必须优先考虑三个地区。这些是Pandeglang,Lebak和Kota Serang。

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