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All Journal Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Gusti Bagus Genta Purusa Arimbawa
Politknik Negeri Bali

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Sistem Rekomendasi Portofolio Berdasarkan Profil Risiko dengan K-Means dan Mean Variance Optimization Gusti Bagus Genta Purusa Arimbawa; Putu Indah Ciptayani; Ni Nyoman Harini Puspita
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 03 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i03.1369

Abstract

The increasing participation of retail investors in Indonesia has not been accompanied by adequate investment decision-making quality. This issue is reflected in fear of missing out behavior and mismatches between investment choices and risk profiles, particularly among beginner investors. This study develops a personalized stock portfolio recommendation system by integrating K-Means Clustering and Mean-Variance Optimization based on investor risk profiles. The analysis covers 39 liquid LQ45 stocks using four years of historical data. The clustering process identified an optimal K value of 4 with a silhouette score of 0.274, resulting in four stock groups: Low Performers, Value & High Dividend, High ROE, and Aggressive Growth. MVO generated three portfolios with Sharpe ratios between 1.19 and 1.21. The aggressive portfolio achieved an expected return of 24.79% with a volatility of 20.53%. The system was implemented as a web application integrating a BCA-standard risk profiling questionnaire and portfolio weight conversion into exchange-compliant lot units. Unlike a previous Fuzzy C-Means-based approach that used one representative stock from each cluster as MVO input, this study optimizes all 39 stocks and incorporates investor risk profile calibration, producing directly executable portfolio recommendations.
Co-Authors Ni Nyoman Harini Puspita Putu Indah Ciptayani