Deep Learning - Prediksi dan Resiko Investasi Enam Saham Bank di Indonesia

Authors

  • Nurdina Widanti
  • Tri Surawan
  • Adhitio Satyo Bayangkari Karno
  • Aji Digdoyo
  • Nani Kurniawati
  • Rachmat Nursalam
  • Harini Agusta

DOI:

https://doi.org/10.31479/jtek.v10i1.194

Abstract

Stock prediction and risk level are important for investors, but this ability can only be done by experts and takes a long time. The rapid development of technology today demands that decisions be made quickly and precisely. Deep Learning (DL) is one of the Artificial Intelligence (AI) methods that are able to analyze and predict stock values accurately, in real-time, and without much human intervention. Analysis of risk and correlation between stocks by calculating daily returns using the moving average (MA) method. Dataset of 6 bank shares obtained from yahoo-finance, namely Bank Central Asia (BBCA), Bank Rakyat Indonesia (BBRI), Bank Mandiri (BMRI), Bank Nasional Indonesia (BBNI), Bank Rakyat Indonesia Syariah (BRIS), and Bank Tabungan Negara (BBTN). The volume of share sales increased significantly only in BBRI and BBNI shares, although 5 bank shares (except BRIS) experienced price increases. The highest correlation occurred between BBNI and BMRI shares with a value of 97%, 92% between BMRI and BBCA shares, and 91% between BBNI and BBCA. Analysis of risk and expected return shows that BRIS has the highest risk and expected return of 0.042245 and 0.002986, respectively. BBCA shares have the lowest risk and expected return at 0.015392 and 0.000695, respectively. The results show that future predictions have decreased, namely BBRI, BBNI, and BBTN, and rose for BBCA, BMRI, and BRIS stocks.

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Published

2022-11-29

Issue

Vol. 10 No. 1 (2022): Jurnal Teknologi

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Articles

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