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APPLICATION OF FUZZY TIME SERIES WITH FIBONACCI RETRACEMENT FOR FORECASTING STOCK PRICE PT. BANK RAKYAT INDONESIA

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 2 (2023) · pp. 0787–0796

DOI
10.30598/barekengvol17iss2pp0787-0796
ISSN
2615-3017, 1978-7227
Published
2023-06-11
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Stock can be defined as securities that indicate the ownership of a person or legal entity to the company issuing the shares. Good stocks for long-term investment are stocks that have good fundamentals and large market capitalization. The purpose of investing is to make a profit. In investing in stocks, investors need to know the risk management that can affect the ups and downs of a stock. Forecasting or forecasting is an analysis to predict everything related to the production, supply, demand, and use of technology in an industry or business. One of the forecasting methods is using fuzzy time series. The primary purpose of fuzzy time series is to predict time series data that can widely use on any real-time data, including capital market data. In this study, we will discuss the evolution of the time series model in overcoming fluctuations that often occur in stock prices by using a fuzzy time series that combines a stock analysis approach, namely Fibonacci retracement. The stock data used in this study is the close price of BBRI for October 2021 to March 2022. Forecasting results for 1 April 2022 are IDR 4660.49 with a Mean Absolute Percentage forecasting accuracy value of 1.034%.

Collaboration network of the authors

19 authors · 61 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Hasanuddin University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nur AfandiHasanuddin University6
Jose RizalAffiliation unknown3
Zulfia Memi MayasariAffiliation unknown2
Vivin AcnesyaAffiliation unknown2
Nurul HidayatiAffiliation unknown2
Ratna WidayatiAffiliation unknown2
Bunga Aulya WarrahmaAffiliation unknown2
Prihatin SihotangAffiliation unknown2
Lidya SavitriAffiliation unknown1
Meca NerdikaAffiliation unknown1
Fajri RamadanAffiliation unknown1
Nova Asri RamdhaniAffiliation unknown1
Fachri FaisalAffiliation unknown1
Mulia AstutiAffiliation unknown1
Refpo RahmanAffiliation unknown1
Ramya RachmawatiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">APPLICATION OF FUZZY TIME SERIES WITH FIBONACCI RETRACEMENT FOR FORECASTING STOCK PRICE PT. BANK RAKYAT INDONESIA</dc:title>
	<dc:creator>Dwi Miranda, Anggel</dc:creator>
	<dc:creator>Yosmar, Siska</dc:creator>
	<dc:creator>Damayanti, Septri</dc:creator>
	<dc:description xml:lang="en-US">Stock can be defined as securities that indicate the ownership of a person or legal entity to the company issuing the shares. Good stocks for long-term investment are stocks that have good fundamentals and large market capitalization. The purpose of investing is to make a profit. In investing in stocks, investors need to know the risk management that can affect the ups and downs of a stock. Forecasting or forecasting is an analysis to predict everything related to the production, supply, demand, and use of technology in an industry or business. One of the forecasting methods is using fuzzy time series. The primary purpose of fuzzy time series is to predict time series data that can widely use on any real-time data, including capital market data. In this study, we will discuss the evolution of the time series model in overcoming fluctuations that often occur in stock prices by using a fuzzy time series that combines a stock analysis approach, namely Fibonacci retracement. The stock data used in this study is the close price of BBRI for October 2021 to March 2022. Forecasting results for 1 April 2022 are IDR 4660.49 with a Mean Absolute Percentage forecasting accuracy value of 1.034%.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-06-11</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7747</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss2pp0787-0796</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications; 0787-0796</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss2year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7747/5939</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Anggel Dwi Miranda, Siska Yosmar, Septri Damayanti</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>