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Open access Jurnal SINTA 2

Peramalan Data IHSG Menggunakan Fuzzy Time Series

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 6 No. 2 (2013)

DOI
10.22146/ijccs.2155
ISSN
2460-7258, 1978-1520
Published
2013-07-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

AbstrakFuzzy time series merupakan salah satu metode soft computing yang telah digunakan dan diterapkan dalam analisis data runtun waktu. Tujuan utama dari fuzzy time series adalah untuk memprediksi data runtun waktu yang dapat digunakan secara luas pada sembarang data real time, termasuk data pasar modal.Banyak peneliti yang telah berkontribusi dalam pengembangan analisis data runtun waktu menggunakan fuzzy time series, seperti Chen dan Hsu [1], Jilani dkk. [2], serta Stevenson dan Porter [3]. Dalam penelitian ini, dicoba untuk menerapkan metode fuzzy time series pada salah satu indikator pergerakan harga saham, yakni data IHSG (Indeks Harga Saham Gabungan).Kinerja metode yang diusulkan dievaluasi dengan menghitung tingkat akurasi dan tingkat kehandalan metode fuzzy time series yang diterapkan pada data IHSG. Melalui pendekatan ini, diharapkan metode fuzzy time series dapat menjadi alternatif untuk memprediksi data IHSG yang merupakan salah satu indikator pergerakan harga saham di Indonesia. Kata kunci – fuzzy time series, data runtun waktu, soft computing, IHSG AbstractFuzzy time series is one of the soft computing method that been used and implemented in time series analysis. The main goal of fuzzy time series is to predict time series data that can be used widely in any real time data, including stock market share.Many researchers have contributed in the development of fuzzy time series analysis, such as Chen and Hsu [1], Jilani [2], and Stevenson and Porter [3]. In this research, we will try to implement the fuzzy time series method in one of the stock market change indicator, i.e. the Jakarta composite index or also known as IHSG (Indeks Harga Saham Gabungan).The research is continued by calculating the accuracy and robustness of the method which has been implemented on IHSG data. By this approach, we hope it can be an alternative to predict the IHSG data which is an indicator of stock price changes in Indonesia. Keywords – fuzzy time series, time series data, soft computing, IHSG

Keywords

Collaboration network of the authors

6 authors · 5 co-authorship links · 1 across different organisations

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

  • Multimedia Nusantara University
  • Universitas Gadjah Mada
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Subanar SubanarUniversitas Gadjah Mada1
Dharma PratamaMultimedia Nusantara University1
Jason ChristianMultimedia Nusantara University1
Santo Sinar PandeanMultimedia Nusantara University1
Naufal Irfan HayantoMultimedia Nusantara University1

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://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Peramalan Data IHSG Menggunakan Fuzzy Time Series</dc:title>
	<dc:creator>Hansun, Seng</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">fuzzy time series; time series data; soft computing; IHSG</dc:subject>
	<dc:description xml:lang="en-US">AbstrakFuzzy time series merupakan salah satu metode soft computing yang telah digunakan dan diterapkan dalam analisis data runtun waktu. Tujuan utama dari fuzzy time series adalah untuk memprediksi data runtun waktu yang dapat digunakan secara luas pada sembarang data real time, termasuk data pasar modal.Banyak peneliti yang telah berkontribusi dalam pengembangan analisis data runtun waktu menggunakan fuzzy time series, seperti Chen dan Hsu [1], Jilani dkk. [2], serta Stevenson dan Porter [3]. Dalam penelitian ini, dicoba untuk menerapkan metode fuzzy time series pada salah satu indikator pergerakan harga saham, yakni data IHSG (Indeks Harga Saham Gabungan).Kinerja metode yang diusulkan dievaluasi dengan menghitung tingkat akurasi dan tingkat kehandalan metode fuzzy time series yang diterapkan pada data IHSG. Melalui pendekatan ini, diharapkan metode fuzzy time series dapat menjadi alternatif untuk memprediksi data IHSG yang merupakan salah satu indikator pergerakan harga saham di Indonesia. Kata kunci – fuzzy time series, data runtun waktu, soft computing, IHSG AbstractFuzzy time series is one of the soft computing method that been used and implemented in time series analysis. The main goal of fuzzy time series is to predict time series data that can be used widely in any real time data, including stock market share.Many researchers have contributed in the development of fuzzy time series analysis, such as Chen and Hsu [1], Jilani [2], and Stevenson and Porter [3]. In this research, we will try to implement the fuzzy time series method in one of the stock market change indicator, i.e. the Jakarta composite index or also known as IHSG (Indeks Harga Saham Gabungan).The research is continued by calculating the accuracy and robustness of the method which has been implemented on IHSG data. By this approach, we hope it can be an alternative to predict the IHSG data which is an indicator of stock price changes in Indonesia. Keywords – fuzzy time series, time series data, soft computing, IHSG</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US">indoceiss</dc:contributor>
	<dc:date>2013-07-31</dc:date>
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	<dc:identifier>10.22146/ijccs.2155</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 6, No 2 (2012): July</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/2155/1935</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2013 IJCCS - Indonesian Journal of Computing and Cybernetics Systems</dc:rights>
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