Diversifikasi Portofolio Saham ESG Quality 45 IDX KEHATI Menggunakan K-Means Clustering

Zalukhu, Michael Jonathan Fritzi (2026) Diversifikasi Portofolio Saham ESG Quality 45 IDX KEHATI Menggunakan K-Means Clustering. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Perkembangan investasi berbasis environmental, social, and governance (ESG) mendorong investor untuk mempertimbangkan aspek sustainability dalam keputusan investasi. Namun, saham-saham dalam indeks ESG tetap memiliki karakteristik return dan risk yang berbeda, sehingga perlu dianalisis sebelum digunakan sebagai dasar pembentukan portofolio. Penelitian ini bertujuan untuk menganalisis karakteristik return dan risk saham konsisten ESG Quality 45 IDX KEHATI menggunakan K-Means Clustering serta menyusun portofolio terdiversifikasi berdasarkan hasil klasterisasi, Sharpe Ratio pada level klaster, dan pembobotan setara. Penelitian ini menggunakan pendekatan kuantitatif deskriptif-eksploratif dengan sampel 20 emiten konsisten ESGQKEHATI selama periode observasi 2022–2024, sedangkan tahun 2025 digunakan sebagai testing period. Data diolah melalui perhitungan monthly return, annual return, annual risk, standardisasi fitur, K-Means Clustering, Silhouette Method, Sharpe Ratio, dan evaluasi performa portofolio. Hasil penelitian menunjukkan bahwa average silhouette score tertinggi diperoleh pada k = 3 sebesar 0,2534. Skenario k = 6 digunakan sebagai pembanding dengan nilai silhouette sebesar 0,2300 karena memberikan segmentasi klaster yang lebih rinci. Portofolio Pilihan 1 dibentuk dari Klaster 3 pada skenario k = 6, sedangkan Portofolio Pilihan 2 dibentuk dari gabungan Klaster 3 dan Klaster 5. Pada testing period 2025, Portofolio Pilihan 1 menghasilkan annual return sebesar 8,44% dengan annualized risk sebesar 21,24%, sedangkan Portofolio Pilihan 2 menghasilkan annual return sebesar 22,39% dengan annualized risk sebesar 22,06%. Portofolio Pilihan 1 menghasilkan return lebih tinggi dibandingkan ESGQKEHATI sebesar 1,42%, tetapi masih berada di bawah IHSG sebesar 22,13%. Adapun Portofolio Pilihan 2 menghasilkan return yang sedikit lebih tinggi dibandingkan IHSG. Temuan ini menunjukkan bahwa K-Means Clustering dapat digunakan sebagai alat bantu analitis untuk memetakan saham ESG berdasarkan karakteristik return dan risk serta mendukung pembentukan portofolio terdiversifikasi
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The development of environmental, social, and governance (ESG)-based investing encourages investors to consider sustainability aspects in investment decision-making. However, stocks included in ESG indices still have different return and risk characteristics, and therefore need to be analyzed before being used as the basis for portfolio construction. This study aims to analyze the return and risk characteristics of consistent ESG Quality 45 IDX KEHATI stocks using K-Means Clustering and to construct a diversified portfolio based on clustering results, cluster-level Sharpe Ratio, and equal weighting. This study employs a descriptive-exploratory quantitative approach with a sample of 20 consistent ESGQKEHATI constituents during the 2022–2024 observation period, while 2025 is used as the testing period. The data are processed through monthly return, annual return, annual risk, feature standardization, K-Means Clustering, Silhouette Method, Sharpe Ratio, and portfolio performance evaluation. The results show that the highest average silhouette score is obtained at k = 3 with a value of 0.2534. The k = 6 scenario is used as a comparative scenario with a silhouette score of 0.2300 because it provides more detailed cluster segmentation. Portfolio Option 1 is formed from Cluster 3 in the k = 6 scenario, while Portfolio Option 2 is formed from the combination of Cluster 3 and Cluster 5. During the 2025 testing period, Portfolio Option 1 generates an annual return of 8.44% with an annualized risk of 21.24%, while Portfolio Option 2 generates an annual return of 22.39% with an annualized risk of 22.06%. Portfolio Option 1 generates a higher return than ESGQKEHATI at 1.42% but remains below IHSG at 22.13%. Portfolio Option 2, meanwhile, generates a slightly higher return than IHSG. These findings indicate that K-Means Clustering can be used as an analytical tool to map ESG stocks based on return and risk characteristics and to support diversified portfolio construction

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Diversifikasi Portofolio, ESG Quality 45 IDX KEHATI, K-Means Clustering, Return dan Risk, Sharpe Ratio, Portfolio Diversification, ESG Quality 45 IDX KEHATI, K-Means Clustering, Return and Risk, Sharpe Ratio
Subjects:	H Social Sciences > HG Finance > HG4529 Investment analysis H Social Sciences > HG Finance > HG4910 Investments H Social Sciences > HG Finance > HG4915 Stocks--Prices Q Science > QA Mathematics > QA278.55 Cluster analysis
Divisions:	Faculty of Creative Design and Digital Business (CREABIZ) > Business Management > 61205-(S1) Undergraduate Thesis
Depositing User:	Michael Jonathan Fritzi Zalukhu
Date Deposited:	01 Aug 2026 06:26
Last Modified:	01 Aug 2026 06:26
URI:	http://repository.its.ac.id/id/eprint/141620

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