The Application Of K-Means Algorithm For LQ45 Index on Indonesia Stock Exchange

ComTech Pub Date : 2016-06-01 DOI:10.21512/COMTECH.V7I2.2256
A. Condrobimo, A. D. Sano, Hendro Nindito
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引用次数: 4

Abstract

The objective of this study is to apply cluster analysis or also known as clustering on stocks data listed in LQ45 index at Indonesia Stock Exchange. The problem is that traders need a tool to speed up decision-making process in buying, selling and holding their stocks.The method used in this cluster analysis is k-means algorithm. The data used in this study were taken from Indonesia Stock Exchange. Cluster analysis in this study took data’s characteristics such as stocks volume and value. Results of cluster analysis were presented in the form of grouping of clusters’ members visually. Therefore, this cluster analysis in this study could be used to identify more quickly and efficiently about the members of each cluster of LQ45 index. The results of such identification can be used by beginner-level investors who have started interest in stock investment to help make decision on stocks trading.
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k -均值算法在印尼证券交易所LQ45指数中的应用
本研究的目的是应用聚类分析或也称为聚类在印度尼西亚证券交易所LQ45指数上市的股票数据。问题在于,交易员需要一种工具来加快买进、卖出和持有股票的决策过程。聚类分析使用的方法是k-means算法。本研究使用的数据来自印度尼西亚证券交易所。本研究的聚类分析采用了存量、价值等数据特征。聚类分析结果以聚类成员分组的形式直观呈现。因此,本研究的聚类分析可以更快速有效地识别LQ45指数各聚类的成员。这种识别的结果可以用于对股票投资产生兴趣的初级投资者,帮助他们做出股票交易决策。
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来源期刊
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0.00%
发文量
6
审稿时长
16 weeks
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