Data mining technique with cluster anaysis use K-means algorithm for LQ45 index on Indonesia stock exchange
作者： A. Raharto Condrobimo , Bahtiar Saleh Abbas , Agung Trisetyarso , Wayan Suparta , Chul-Ho Kang
DOI: 10.1109/ICOIACT.2018.8350820
关键词: Stock (geology) 、 Data mining 、 k-means clustering 、 Stock exchange 、 Cluster analysis 、 Cluster based 、 Computer science 、 Stock trading 、 Identifier
摘要: This study aims to apply data mining techniques with cluster analysis on stock registered in LQ45 Indonesia Stock Exchange. The used this method is k-means algorithm, the research taken from analyzed characteristics of volumes and values, while results were presented form members visually. Therefore, can be for quick efficient identifier each member index based share value its volume. identification by beginner-level investors that begun interested investments help make informed decisions about trading desired groups.
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