SCREENING SAHAM SYARIAH DENGAN HIERARICAL DENDOGRAM

Muhlasah Novitasari Mara, Halmi Helmi, Aisyatul Karimah, Mirasanti Wahyuni

Abstract


The COVID-19 pandemic has hit various sectors including the stock market. It is undeniable that the COVID-19 pandemic raises concerns and doubts about investing, given that uncertain conditions make volatility even higher. Nevertheless, the number of capital market investors in Indonesia increased by 42% at the end of 2020 compared to the previous year. The increase in the number of investors also occurred in Southeast Asian countries. The COVID-19 pandemic that hit the world has made people more careful in using their money. The allocation of public funds that was previously consumptive, during the pandemic began to be directed to invest, one of which was investment in the capital market. Jakarta Composite Index (JCI) data shows that JCI has been able to recover for the last one year since the COVID-19 pandemic hit Indonesia. This indicates that stock investments are still able to provide profits during the pandemic. Although the JCI shows a recovery, it does not mean that the stock value of all issuers has recovered. Therefore, the right sector and stock selection strategy for investment needs to be implemented in order to have the opportunity to get profits. The difficulty for investors in stock screening is that investors have to analyze one by one for each issuer. In this study, machine learning screening with the Herarical Dendogram method will be used to select Islamic stocks listed in the Jakarta Islamic Index (JII).

Keywords


Clustering; JII30; Emiten; Machine Learning; Return; Stocks Screening

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