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All Journal Zero : Jurnal Sains, Matematika, dan Terapan
Wirda Andani
Department of Statistics, Tanjungpura University, Pontianak, Indonesia
Agriculture, Biological Sciences & Forestry Chemistry Mathematics Physics

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IDX30 Portfolio Construction using K-Means Clustering with MAD Risk Optimization and Sortino Ratio Evaluation Rifki Pebriyandi; Evy Sulistianingsih; Hendra Perdana; Wirda Andani; Shantika Martha
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 2 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i2.28613

Abstract

A stock portfolio plays an important role in managing risk and achieving optimal returns in volatile markets. This study proposes an integrated framework that combines K-Means Clustering, Mean Absolute Deviation (MAD), and the Sortino Ratio. The main contribution lies in linking clustering-based asset selection with downside risk optimization and evaluation, enabling portfolio construction that accounts for asset similarity, risk measurement, and investor-oriented performance assessment. This approach addresses the limitation of previous studies that apply these methods separately by providing a more structured basis for downside risk-adjusted portfolio selection. Using daily IDX30 stock data from June 2024 to June 2025, samples were selected based on index consistency. The results indicate that a portfolio of ANTM and INDF achieved the highest Sortino Ratio of 0.2179. These findings suggest that combining high-return stocks with moderate volatility, supported by clustering and downside risk optimization, can improve downside risk-adjusted performance, providing practical guidance for investors.
Co-Authors Evy Sulistianingsih Hendra Perdana Rifki Pebriyandi Shantika Martha