Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms

Enes Filiz

doi:10.34110/forecasting.1863623

Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms

Abstract

In the globalizing world order, different sectors are affected by global events. The manufacturing sector is one of the most critical sectors for both individual countries and the world at large. The development of this sector alleviates the economic burden on countries and helps them gain economic independence. In this context, this study aims to forecast the future values of Türkiye's manufacturing industry capacity utilization rate. To this end, monthly data from June 2013 to December 2024 were used to forecast all months of 2025. The Random Tree and Random Forest Algorithms, which are machine learning algorithms, were employed for this forecasting process. As a result of the study, the Random Tree algorithm showed a better forecasting performance with an accuracy of 83.48%. Furthermore, the Correlation Attribute Feature Selection Algorithm was used to identify the variables affecting the prediction of Türkiye's manufacturing industry capacity utilization rate. These variables were determined to be ‘Manufacture of electrical equipment’, ‘Non-Durable Consumer Goods’, ‘Investment Goods’, and ‘Durable Consumer Goods’, respectively.

Keywords

Supporting Institution

No

Ethical Statement

This study does not require Ethics Committee approval.

Thanks

NO

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Details

Primary Language

English

Subjects

Machine Learning (Other), Statistics (Other)

Journal Section

Research Article

Authors

Enes Filiz ^*
0000-0002-8006-9467
Türkiye

Publication Date

September 14, 2026

Submission Date

January 14, 2026

Acceptance Date

May 30, 2026

Published in Issue

Year 2026 Volume: 10 Number: 2

DOI

https://doi.org/10.34110/forecasting.1863623

IZ

https://izlik.org/JA24CR43ML

Cite

RIS / Bibtex

APA

Filiz, E. (2026). Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms. Turkish Journal of Forecasting, 10(2), 69-82. https://doi.org/10.34110/forecasting.1863623

AMA

1.Filiz E. Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms. TJF. 2026;10(2):69-82. doi:10.34110/forecasting.1863623

Chicago

Filiz, Enes. 2026. “Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms”. Turkish Journal of Forecasting 10 (2): 69-82. https://doi.org/10.34110/forecasting.1863623.

EndNote

Filiz E (September 1, 2026) Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms. Turkish Journal of Forecasting 10 2 69–82.

IEEE

[1]E. Filiz, “Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms”, TJF, vol. 10, no. 2, pp. 69–82, Sept. 2026, doi: 10.34110/forecasting.1863623.

ISNAD

Filiz, Enes. “Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms”. Turkish Journal of Forecasting 10/2 (September 1, 2026): 69-82. https://doi.org/10.34110/forecasting.1863623.

JAMA

1.Filiz E. Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms. TJF. 2026;10:69–82.

MLA

Filiz, Enes. “Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms”. Turkish Journal of Forecasting, vol. 10, no. 2, Sept. 2026, pp. 69-82, doi:10.34110/forecasting.1863623.

Vancouver

1.Enes Filiz. Analysis of Manufacturing Industry Capacity Utilization Rate Forecasts Using Decision Tree-Based Algorithms. TJF. 2026 Sep. 1;10(2):69-82. doi:10.34110/forecasting.1863623