Doğal Gaz Tesisat Firmalarının Gelecek İş Hacminin Tahmini: Mevsimsel ve Kısa Vadeli Dinamiklerin Mevsimsel Otoregresif Entegre Hareketli Ortalama (SARIMA) Modeli ile Analizi

Yıl 2026, Cilt: 41 Sayı: 1, 241 - 252, 25.03.2026

Selin Saraç Güleryüz , Fikri Ege

https://doi.org/10.21605/cukurovaumfd.1781580

https://izlik.org/JA26HP46EA

Öz

Bu çalışmada Mersin ilindeki doğal gaz tesisat firmalarının gelecekteki iş hacimleri zaman serisi yöntemleri kullanılarak tahmin edilmiştir. Mevsimsel Otoregresif Entegre Hareketli Ortalama (SARIMA) modeli, mevsimsel bileşenlerin ve kısa vadeli dinamiklerin modellenmesi için kullanılmıştır. 2011 yılından itibaren 10 yıl boyunca toplanan aylık yeni abone sayısı verisi analiz edilmiştir. Durağanlık ADF testi ile sınanmış, model parametreleri ACF ve PACF grafikleri incelenerek (1,0,0)(0,1,2)[12] olarak belirlenmiştir. Modelin doğruluğu MAPE ve R² kriterleri ile değerlendirilmiş; sırasıyla %16,51 ve 0,81 değerleri elde edilmiştir. Tahmin sonuçları, mevsimsel değişimlerin işletme planlamalarında belirleyici bir rol oynadığını göstermekte; firmaların insan kaynakları, stok yönetimi ve pazarlama stratejilerinde mevsimselliği esas almaları gerektiğini ortaya koymaktadır. Bu çalışma, doğal gaz tesisat sektöründeki işletmelere stratejik karar alma süreçlerinde uygulanabilir ve veri temelli bilgiler sunmaktadır.

Anahtar Kelimeler

Zaman serisi tahminleme , ARIMA , Doğal gaz , İş hacmi

Forecasting Future Business Volume of Natural Gas Installation Companies: Analysis of Seasonal and Short-Term Dynamics Using the Seasonal Autoregressive Integrated Moving Average (SARIMA) Model

https://izlik.org/JA26HP46EA

Öz

This study forecasts the future business volume of natural gas installation companies in Mersin province using time series methods. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was employed to capture seasonal components and short-term dynamics. Monthly new subscriber data collected over a 10-year period starting from 2011 were analyzed. Stationarity was verified using the Augmented Dickey-Fuller (ADF) test, and model parameters were identified as (1,0,0) (0,1,2)[12] through ACF and PACF analysis. Model accuracy was assessed via MAPE and R², yielding values of 16.51% and 0.81, respectively. The results reveal that seasonal fluctuations in natural gas demand play a decisive role in business planning, highlighting the need for companies to incorporate seasonality into human resources, inventory, and marketing decisions. This study provides actionable and data-driven insights for strategic decision-making in the natural gas installation sector.

Anahtar Kelimeler

Time series forecasting , ARIMA , Natural gas , Business volume

Kaynakça

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