Turkish Journal of Agriculture and Forestry
Abstract
In this study, it was aimed to predict Türkiye’s furniture exports for the period from January 2010 to May 2025 using machine learning methods based on macroeconomic indicators. The dataset consisted of 10 economic variables, including the furniture industry production index, capacity utilization rate, import volume, total exports, real effective exchange rate, producer price index, money supply, and oil prices, with 185 observations per variable and a total of 2035 data points. During the data preprocessing phase, no missing or outlier values were detected, and the data were divided into 70% training and 30% testing subsets. Decision tree, random forest, and deep learning models were developed using the software RapidMiner Studio, and hyperparameter optimization was performed through the grid search method. Model performances were evaluated using root mean square deviation, mean absolute error, mean absolute percentage error, and R2 metrics. The results indicated that all models predicted furniture exports with high accuracy. The best performance was achieved by the random forest model, with R2 = 0.977 and MAPE = 5.28% in the testing phase. Furthermore, the variable importance analysis based on the random forest model revealed that the furniture industry production index and capacity utilization rate were the most significant determinants of exports, highlighting the production-driven nature of the sector. These findings demonstrate that machine learning methods can be effectively used in forecasting economic indicators and that Türkiye’s furniture exports can be reliably predicted through data-driven approaches.
Author ORCID Identifier
İLKER AKYÜZ: 0000-0003-4241-1118
NADİR ERSEN: 0000-0003-3643-1390
TİMUÇİN BARDAK: 0000-0002-1403-1049
SELAHATTİN BARDAK: 0000-0001-9724-4762
DOI
10.55730/1300-011X.3355
Keywords
Furniture sector, deep learning, random forest, decision tree
First Page
342
Last Page
356
Publisher
The Scientific and Technological Research Council of Türkiye (TÜBİTAK)
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
AKYÜZ, İ, ERSEN, N, BARDAK, T, & BARDAK, S (2026). Prediction of furniture exports in Türkiye using machine learning methods. Turkish Journal of Agriculture and Forestry 50 (3): 342-356. https://doi.org/10.55730/1300-011X.3355
