采用K-means算法对印尼证券交易所LQ45指数进行聚类分析

2018 International Conference on Information and Communications Technology (ICOIACT) Pub Date : 2018-04-26 DOI:10.1109/ICOIACT.2018.8350820

A. Condrobimo, B. S. Abbas, A. Trisetyarso, W. Suparta, C. Kang

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引用次数: 5

摘要

本研究旨在将数据挖掘技术与聚类分析应用于印尼证券交易所LQ45注册的股票数据。本方法采用k-means算法进行聚类分析，本研究数据来源于印度尼西亚证券交易所。本研究的聚类分析分析了数据量和存量值的特征，而本研究的结果以聚类成员的形式直观地呈现出来。因此，本研究中的聚类分析可以基于每个聚类的份额值及其体积对LQ45索引聚类的每个成员进行快速有效的识别。识别结果可用于开始对股票投资感兴趣的初级投资者，以帮助他们在期望的群集组上做出明智的股票交易决策。

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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Data mining technique with cluster anaysis use K-means algorithm for LQ45 index on Indonesia stock exchange

This study aims to apply data mining techniques with cluster analysis on stock data registered in LQ45 in Indonesia Stock Exchange. The cluster analysis used in this method is k-means algorithm, the data in this research is taken from Indonesia Stock Exchange. The cluster analysis in this study analyzed the characteristics of data volumes and stock values, while the results in this study were presented in the form of cluster members visually. Therefore, this cluster analysis in this research can be used for quick and efficient identifier for each member of LQ45 index cluster based on share value for each cluster and its volume. The identification results can be used by beginner-level investors that begun to be interested in stock investments to help make informed decisions about stock trading on desired cluster groups.

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来源期刊

2018 International Conference on Information and Communications Technology (ICOIACT)

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