Issue |
BIO Web Conf.
Volume 171, 2025
The Frontier in Sustainable Agromaritime and Environmental Development Conference (FiSAED 2024)
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|
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Article Number | 04003 | |
Number of page(s) | 15 | |
Section | Socio-economic Transformation for Sustainable Agromaritime | |
DOI | https://doi.org/10.1051/bioconf/202517104003 | |
Published online | 04 April 2025 |
Selection of agricultural industry stocks by application of K-means algorithm with Elbow method
Faculty of Economics and Management, IPB University, Jl. Agatis. Dramaga Campus IPB, Bogor, West Java, 16680, Indonesia
* Corresponding author: alimu@apps.ipb.ac.id
Portfolio concentration is investing in assets with specific characteristics within the same sector. Agricultural product industry stocks can be used as an option to form portfolio concentration because they have good growth and performance. This study aims to cluster agricultural product industry stocks listed on the Indonesia Stock Exchange from 2020-2023 using the K-Means clustering algorithm with the Elbow method using the Python 3.10 analysis tool to determine clusters that contain a collection of stocks with the best financial performance. The research resulted in an optimal number of clusters of 3, namely cluster 0, 1, and 2. The cluster that contains a collection of stocks with the best financial performance is cluster 2, which is filled by BISI, LSIP, and DPUM. Cluster 1 has several stocks with relatively good financial performance as it is adjacent to cluster 2, namely AALI, STAA, and CPIN.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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