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K-Means clustering with Decision Support System using SAW: Determining thesis topic

机译:使用SAW的带有决策支持系统的K-Means聚类:确定论文主题

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Thesis is an essential requirement for students to graduate. Students choose thesis topic according to their interests. In fact, many students choose inappropriate topic for their thesis and cause their thesis quality are bad. One of ways to solve the problem is to develop information system in form of Decision Support System (DSS). DSS needs data modeling and process to generate alternative decisions. Data modeling is in form of clustering using K-Means. This process generates clusters and weights to each topic. Weight is used to generate alternative decisions using Simple Additive Weighting Method. Combination K-Means and SAW can generate calculation fast to produce alternative decisions. This solution to support topic selection is excepted to contribute choosing thesis topic according to students ability.
机译:论文是学生毕业的基本要求。学生根据自己的兴趣选择论文主题。实际上,许多学生为自己的论文选择了不合适的主题,从而导致他们的论文质量很差。解决问题的一种方法是开发决策支持系统(DSS)形式的信息系统。 DSS需要数据建模和流程来生成替代决策。数据建模是使用K-Means进行聚类的形式。此过程为每个主题生成聚类和权重。权重用于使用简单加法加权法生成替代决策。 K均值和SAW的组合可以快速生成计算以产生替代决策。该支持主题选择的解决方案不包括根据学生的能力来帮助选择论文主题。

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