The Application Of K-Means Algorithm For LQ45 Index on Indonesia Stock Exchange
DOI:
https://doi.org/10.21512/comtech.v7i2.2256Keywords:
blue chip stock, data mining, k-means, clusteringAbstract
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.
Plum Analytics
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