A Comparative Analysis of Interval Determination Using Sturges’ Rule and the Average-Based Method in Chen’s Fuzzy Time Series Model for Forecasting Indonesia’s CO_2 Emissions.

Authors

  • Vivianti Vivianti Postgraduate Program in Statistics, Universitas Negeri Makassar
  • Aswi Aswi Universitas Negeri Makassar

DOI:

https://doi.org/10.24252/msa.v14i2.66114

Keywords:

Fuzzy Time Series Chen, interval determination, Sturges method, mean-based methodv, greenhouse gas emissions

Abstract

Forecasting greenhouse gas (GHG) emissions plays a crucial role in supporting mitigation efforts against global climate change. One widely used method for forecasting nonlinear time series data is the Fuzzy Time Series (FTS) Chen model. However, the accuracy of this model is significantly influenced by the interval determination method applied during the fuzzification process. This study aims to compare the forecasting accuracy of the FTS Cheng model using two interval determination approaches: the Sturges method and the mean-based method. The data employed consist of Indonesia’s carbon emissions from 1960 to 2022. The results indicate that the mean-based method yields more accurate forecasting outcomes than the Sturges method, as reflected by a lower MAPE of 5.602 and RMSE of 10.056, compared to MAPE of 86.986 and RMSE of 59.792 for the Sturges method. Based on the forecasting results, Indonesia’s carbon emissions in 2023 are predicted to reach 724.86 MtCO₂ using the mean-based method, whereas the Sturges method predicts 577.28 MtCO₂. These findings highlight that the choice of interval determination method plays a critical role in improving the forecasting accuracy of the FTS modelv

Author Biography

Aswi Aswi, Universitas Negeri Makassar

Statistika

References

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Published

2026-10-31

How to Cite

[1]
V. Vivianti and A. Aswi, “A Comparative Analysis of Interval Determination Using Sturges’ Rule and the Average-Based Method in Chen’s Fuzzy Time Series Model for Forecasting Indonesia’s CO_2 Emissions”., MSA, vol. 14, no. 2, pp. 235–247, Oct. 2026.

Issue

Vol. 14 No. 2 (2026): Volume 14 No 2, 2026

Section

Artikel

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Copyright (c) 2026 Vivianti Vivianti, Aswi Aswi

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