Optimasi Pemilihan Portofolio Pada Saham IDX LQ45 Low Carbon Leaders Menggunakan Fuzzy Multiobjective Linear Programming

Fajarwati, Amila (2024) Optimasi Pemilihan Portofolio Pada Saham IDX LQ45 Low Carbon Leaders Menggunakan Fuzzy Multiobjective Linear Programming. Diploma thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pasar modal berperan penting dalam penanganan perubahan iklim di Indonesia dengan mengalihkan investasi ke sektor energi bersih. Komitmen pemerintah tercermin dalam peluncuran indeks IDX LQ45 low carbon leaders. Penelitian ini bertujuan menganalisis proporsi portofolio saham optimal pada indeks tersebut dengan menggunakan metode k-means clustering untuk mengelompokkan saham berdasarkan karakteristik tertentu. Diversifikasi ini berfokus pada pengurangan risiko dan optimal keuntungan. Untuk mengatasi hal ini, digunakan metode Fuzzy Multiobjective Linear Programming (FMOLP), yang memanfaatkan data historis harga saham guna menghasilkan portofolio optimal. Hasil penelitian menunjukkan bahwa clustering saham menghasilkan dua cluster optimum, dengan silhouette score tertinggi sebesar 0,400. Cluster pertama terdiri dari sembilan perusahaan, sementara cluster kedua mencakup tiga perusahaan. Analisis karakteristik cluster menunjukkan bahwa cluster kedua memiliki kinerja keuangan yang lebih unggul dalam berbagai indikator, seperti dividend yield, return on assets, return on equity, dan time interest earned. Oleh karena itu, saham-saham dalam cluster kedua diprioritaskan untuk analisis lanjutan menggunakan metode fuzzy multi-objective linear programming. Portofolio optimal yang dibentuk terdiri dari tiga saham: AKRA (10%), AMRT (45%), dan UNTR (45%). Portofolio ini diharapkan menghasilkan return sebesar 1,177% per bulan dengan risiko 2,833% per bulan, lebih rendah dibandingkan risiko saham individu. Evaluasi dengan Sharpe ratio menunjukkan nilai 23,916%, jauh lebih tinggi dibandingkan saham individu (AKRA 0,613%, AMRT 0,769%, UNTR 3,611%), yang mengindikasikan bahwa strategi ini berhasil mengurangi risiko dan memaksimalkan keuntungan per unit risiko yang diambil.
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The capital market plays an important role in addressing climate change in Indonesia by shifting investments to the clean energy sector. The government’s commitment is reflected in the launch of the IDX LQ45 low carbon leaders index. This study aims to analyze the proportion of an optimal stock portfolio in the index by using the k-means clustering method to group stocks based on specific characteristics. This diversification focuses on risk reduction and optimizing returns. To address this, the Fuzzy Multiobjective Linear Programming (FMOLP) method is used, which utilizes historical stock price data to generate an optimal portfolio. The results show that stock clustering generates two optimal clusters, with the highest silhouette score of 0.400. The first cluster consists of nine companies, while the second cluster includes three companies. Cluster characteristic analysis shows that the second cluster has superior financial performance in various indicators, such as dividend yield, return on assets, return on equity, and times interest earned. Therefore, the stocks in the second cluster are prioritized for further analysis using the fuzzy multi-objective linear programming method. The optimal portfolio formed consists of three stocks: AKRA (10%), AMRT (45%), and UNTR (45%). This portfolio is expected to generate a return of 1.177% per month with a risk of 2.833% per month, which is lower compared to the individual stock risks. Evaluation with the Sharpe ratio shows a value of 23.916%, much higher than the individual stocks (AKRA 0.613%, AMRT 0.769%, UNTR 3.611%), indicating that this strategy successfully reduces risk while maximizing returns per unit of risk taken.

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	Fuzzy Multiobjective Linear Programming, IDX LQ45 Low Carbon Leaders, Investasi, Portofolio Saham, Investment, Stock Portfolio.
Subjects:	H Social Sciences > HG Finance > HG4529 Investment analysis H Social Sciences > HG Finance > HG4529.5 Portfolio management Q Science > QA Mathematics > QA278.55 Cluster analysis Q Science > QA Mathematics > QA9.64 Fuzzy logic
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Amila Fajarwati
Date Deposited:	20 Dec 2024 03:31
Last Modified:	20 Dec 2024 03:31
URI:	http://repository.its.ac.id/id/eprint/116021

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