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DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM

Cilt: 11 Sayı: 2 15 Ekim 2026
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DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM

Öz

The growing global resource scarcity is increasing the importance of exports for countries. Countries must be prepared for any potential problems that may occur. To this end, they must prioritize their export strategies. A country’s ability to be self-sufficient through exports demonstrates its level of development. As exports grow economic challenges decrease while national welfare improves. This study aims to predict Türkiye's export unit value index. Monthly data from April 2013 to December 2024 from the Central Bank of the Republic of Türkiye is used in the study. The M5 rules machine learning algorithm will be used to predict Türkiye's export unit value index. The correlation-based (Cfs Subset) feature selection algorithm was included to identify the effective variables the prediction of Türkiye's export unit value index. The results of the analysis with the Weka program demonstrate that M5 rules machine learning was successful in making predictions using both all variables and effective variables. Furthermore, the effective variables the prediction of Türkiye's export unit value index were found to be ‘Investment Goods (Excluding Transportation Vehicles)’, ‘Raw Materials (Intermediate Goods)’, ‘Unprocessed Industrial Raw Materials’, ‘Consumer Goods’, and ‘Food and Beverage-Based Processed Consumer Goods’.

Anahtar Kelimeler

M5 rules machine learning algorithm, Prediction, Correlation-based feature selection algorithm, Export unit value index

Destekleyen Kurum

No

Etik Beyan

The author declare that ethical rules were followed throughout the preparation of this study. In the event that any violation is detected, Journal of Academic Projection bears no responsibility, and all responsibility lies with the authors of the study.

Teşekkür

No

Kaynakça

  1. Abdelsamiea, A. T., El-Aal, A., & Mohamed, F. (2025). Industrial exports and global carbon emissions: assessing the impact of the US and China using a decision tree algorithm. International Journal of Energy Economics and Policy, 15(6), 281-286.
  2. Al Khaldy, M. (2024, July). Correlation-Based Feature Selection for Enhanced Arrhythmia Classification. In International Conference on Intelligent and Fuzzy Systems (pp. 355-364). Cham: Springer Nature. Switzerland. Athukorala, P. C., & Sen, K. (1998). Processed food exports from developing countries: patterns and determinants. Food Policy, 23(1), 41-54.
  3. Augustine, M., & Runge, C. (2025). Impact of Money Supply on Export Price Index. Available at SSRN 5259451. http://dx.doi.org/10.2139/ssrn.5259451
  4. Ayaz, Y., Kocamaz, A. F., & Karakoç, M. B. (2015). Modeling of compressive strength and UPV of high-volume mineral-admixtured concrete using rule-based M5 rule and tree model M5P classifiers. Construction and Building Materials, 94, 235-240.
  5. Betai, N. V., & Chanda, R. (2020). Global value chain participation and intermediate export sophistication. IIM Bangalore Research Paper, (629). http://dx.doi.org/10.2139/ssrn.3724329
  6. Bui, D. T., Bui, K. T. T., Minh, N. Q., Ha, N. V., Van Chinh, D., & Revhaug, I. (2017). A comparative asessment of multi-layer perceptron neural networks and M5-rules algorithm for modeling and forecasting of horizontal displacement of the Hoa Binh hydropower dam (Vietnam). In The international symposium on geo-spatial and mobile mapping technology (GMMT2016). Hanoi.
  7. Buturac, G. (2009). Structural characteristics of exports and imports of Croatian manufacturing. Ekonomski pregled, 60(9-10), 432-457.
  8. Central Bank of the Republic of Turkey Web Page. (2025). Türkiye Export Unit Value Index. Access date: 25.12.2025: https://evds2.tcmb.gov.tr/index.php?/evds/serieMarket/#collapse_2.
  9. Chand, K. S. P., Prabakaran, N., Ramani, S., Rao, D. V., & Vemparala, S. (2020). Assessment analysis and performance prediction using M5 rules. International Journal of Recent Technology and Engineering, 8(4), 12945-12951.
  10. Curtis, A., & McLellan, B. (2023). Framework for Assessment of the Economic Vulnerability of Energy-Resource-Exporting Countries. Resources, 12(2), 27.

Kaynak Göster

APA
Filiz, E. (2026). DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM. Akademik İzdüşüm Dergisi, 11(2), 108-121. https://izlik.org/JA68LW56HN
AMA
1.Filiz E. DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM. AİD. 2026;11(2):108-121. https://izlik.org/JA68LW56HN
Chicago
Filiz, Enes. 2026. “DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM”. Akademik İzdüşüm Dergisi 11 (2): 108-21. https://izlik.org/JA68LW56HN.
EndNote
Filiz E (01 Ekim 2026) DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM. Akademik İzdüşüm Dergisi 11 2 108–121.
IEEE
[1]E. Filiz, “DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM”, AİD, c. 11, sy 2, ss. 108–121, Eki. 2026, [çevrimiçi]. Erişim adresi: https://izlik.org/JA68LW56HN
ISNAD
Filiz, Enes. “DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM”. Akademik İzdüşüm Dergisi 11/2 (01 Ekim 2026): 108-121. https://izlik.org/JA68LW56HN.
JAMA
1.Filiz E. DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM. AİD. 2026;11:108–121.
MLA
Filiz, Enes. “DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM”. Akademik İzdüşüm Dergisi, c. 11, sy 2, Ekim 2026, ss. 108-21, https://izlik.org/JA68LW56HN.
Vancouver
1.Enes Filiz. DETERMINING THE PREDICTION OF THE EXPORT UNIT VALUE INDEX USING THE M5 RULES MACHINE LEARNING ALGORITHM. AİD [Internet]. 01 Ekim 2026;11(2):108-21. Erişim adresi: https://izlik.org/JA68LW56HN