<![CDATA[Purpose: This research aimed to find the effect of cluster techniques in determining stock selection to maximize return and minimize risk in the stock market. Research Methodology: The methodology consists of two of several algorithmic approaches of the clustering method to find hidden patterns in a group of datasets, i.e., Partitioning clusters (k-means) defined by the dataset object and its central area, and hierarchical clusters that group data through varying scales to be implemented into cluster trees or dendrogram. Dataset summary analysis of the fundamental ratio of stocks in the study was obtained from IDX stock data. Results: This study's classification has been obtained that consists of three zones: green, blue and red zone. The significance obtained provides an alternative form of stock categorization, creating an investment decision support system based on Cluster Analysis, the search for correlations and patterns between ratios of the Financial Statements as complementary tools of Investment Risk Management. Limitations: This research uses only two clustering algorithm methods to analyze the effect of clustering in maximizing return and minimizing risk and only used variables of financial reports for the company listed on the Indonesia Stock Exchange. Contribution: The risk management portfolio is a crucial part of being analyzed for investors and management to improve financial performance. As a complement to decision support, the risk management systems have to be analyzed based on cluster analysis and subsequent data mining to know the potential stock valuation in the market.]]>
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