Triangular Fuzzy Time Series for Two Factors High-order based on Interval Variations

Authors

  • A. Nafis Haikal Department of Mathematics, Universitas Diponegoro
  • Etna Vianita Department of Mathematics, Universitas Diponegoro http://orcid.org/0000-0002-6773-4995
  • Muhammad Sam'an Department of Informatics, Universitas Muhammadiyah Semarang
  • Bayu Surarso Department of Mathematics, Universitas Diponegoro
  • Susilo Hariyanto Department of Mathematics, Universitas Diponegoro

DOI:

https://doi.org/10.31764/jtam.v6i3.8627

Keywords:

Forecasting, Fuzzy Time Series, Triangular Fuzzy Number, Intervals ratio.

Abstract

Fuzzy time series (FTS) firstly introduced by Song and Chissom has been developed to forecast such as enrollment data, stock index, air pollution, etc. In forecasting FTS data several authors define universe of discourse using coefficient values with any integer or real number as a substitute. This study focuses on interval variation in order to get better evaluation. Coefficient values analyzed and compared in unequal partition intervals and equal partition intervals with base and triangular fuzzy membership functions applied in two factors high-order. The study implemented in the Shen-hu stock index data. The models evaluated by average forecasting error rate (AFER) and compared with existing methods. AFER value 0.28% for Shen-hu stock index daily data. Based on the result, this research can be used as a reference to determine the better interval and degree membership value in the fuzzy time series.

 

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Published

2022-07-16

Issue

Vol. 6 No. 3 (2022): July

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