Seleksi Portofolio Saham Emiten Anggota LQ45 Menggunakan K-Means Clustering Berdasarkan Pendekatan Teknikal Dan Fundamental : Studi Kasus Pandemi Covid-19

Riyadhi, Atha Fitrah (2023) Seleksi Portofolio Saham Emiten Anggota LQ45 Menggunakan K-Means Clustering Berdasarkan Pendekatan Teknikal Dan Fundamental : Studi Kasus Pandemi Covid-19. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

COVID – 19 telah memberikan dampak negatif kepada pertumbuhan perekonomian di Indonesia dan mempengaruhi tingkat ketidakpastian investasi dalam pasar modal Indonesia. Saham-saham unggulan dengan kapitalisasi pasar besar dan masuk dalam indeks saham LQ45 di Bursa Efek Indonesia (BEI) juga terkena imbas akibat dari pandemi COVID-19 yang terkoreksi sebesar -15% dari masa sebelum pandemi. Penurunan signifikan tersebut memiliki dampak negatif langsung kepada investor pasar modal sehingga untuk menghindari peristiwa Black Swan yang terjadi diakibatkan oleh resesi , investor perlu melakukan diversifikasi portofolio. Maka dari itu, penelitian ini bertujuan untuk membantu investor dalam melakukan diversifikasi portofolio yang lebih baik khususnya dalam menghadapi masa pandemi dengan menggunakan metode klasterisasi. Dilakukan klasterisasi pada 35 Saham yang termasuk anggota Indeks LQ45 sejak 1 Januari 2019 hingga 31 Desember 2020 berdasarkan indikator fundamental bisnis dan juga teknikal saham menggunakan algoritma K-Means Clustering. Hasil temuan dari metode klasterisai menunjukkan bahwa saham LQ45 dikelompokkan menjadi 4 klaster yang masing-masing memiliki sifat yang berbeda. Selanjutnya hasil klasterisasi tersebut digunakan sebagai acuan dalam pembentukan portofolio dimana saham yang memiliki sharpe ratio terbaik dari setiap klaster pilihan akan dipilih untuk membentuk portofolio. Dari hasil analisa pengujian performa portofolio sepanjang periode market tahun 2021, didapatkan bahwa portofolio yang telah dibentuk dari hasil klasterisasi dinilai berperforma sangat baik dikarenakan memiliki return positif dan lebih baik dari performa indeks LQ45 secara makro. Selain itu, portofolio tersebut juga sudah terdiversifikasi dengan baik dibuktikan dengan nilai korelasi antar sahamnya yang berkorelasi rendah. Penggunaan metode klasterisasi dinilai efektif dalam membagi saham sesuai sifat fundamental & pergerakan harganya sebagai bagian dari proses diversifikasi portofolio saham.
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COVID-19 has had a negative impact on economic growth in Indonesia and affected level of investment uncertainty in the Indonesian capital market. Leading stocks with large market capitalization and included in the LQ45 stock index on the Indonesia Stock Exchange (IDX) were also affected by the COVID-19 pandemic, which was corrected by -15% from the pre-pandemic period. This significant decline has a direct negative impact on capital market investors, so to avoid the Black Swan event that occurred due to the recession, investors need to diversify their portfolios. Therefore, this study aims to assist investors in better portfolio diversification, especially in the face of the pandemic by using the clustering method. Clustering was carried out on 35 stocks that are members of LQ45 Index from January 1, 2019 to December 31, 2020 based on business fundamental and technical indicators stocks using the K-Means Clustering algorithm. The findings from the clustering method show that LQ45 stocks are grouped into 4 clusters, each of which has different characteristics. Furthermore, the results of the clustering are used as a reference in the formation of a portfolio where the stocks which have the best sharpe ratio from each selected cluster will be selected to form a portfolio. From the results of the analysis of portfolio performance testing throughout the market period in 2021, study found that the portfolio that was formed from the results of the clustering is having good performance because it has a positive return and looks much better comparing to LQ45 index as a macro evalutation . In addition, portfolio has also been well diversified, as evidenced by the low correlation value of its inter-stock correlation. Application of clustering method is considered effective in dividing stocks according to their fundamental nature and price movements as part of the stock portfolio diversification process.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Portofolio Investasi, K-Means Clustering, Index LQ45, Machine Learning, COVID-19
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD38.7 Business intelligence. Trade secrets Q Science > Q Science (General) > Q325.5 Machine learning. Support vector machines. Q Science > QA Mathematics > QA278.55 Cluster analysis
Divisions:	Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT)
Depositing User:	Atha Fitrah Riyadhi
Date Deposited:	08 Feb 2023 08:42
Last Modified:	08 Feb 2023 08:42
URI:	http://repository.its.ac.id/id/eprint/96535

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