Türkiye’de Turizm Tahmini İçin Holt-Winters ve SARIMA Modellerinin Performanslarının Karşılaştırılması

Yıl 2020, Cilt: 21 Sayı: 2, 63 - 77, 01.07.2020

Wael Zayat Bahar Sennaroglu

Öz

Türkiye’ye gelen turist sayısını tahmin etmek hem özel sektör hem de kamu sektörü için stratejik planlamada çok önemli bir rol oynayabilir. Bu çalışmada, Türkiye’yi ziyaret eden yabancıların sayısı 2007 ve 2018 yılları arasında aylık olarak alınmıştır. Veri artan bir eğilim ile mevsimsel davranış göstermektedir, bu nedenle çalışma için iki metot seçilmiştir: Holt-Winters HW and Seasonal Autoregressive Integrated Moving Average SARIMA . Çalışmanın amacı iyi bir seviyede tahmin doğruluğu elde etmek için en uygun tahmin modelini belirlemektir. Sonuçlar bütün modellerin hata ölçümlerine göre doğru tahmin değerleri verdiğini göstermiştir. Bununla birlikte, HW çarpımsal modeli en yüksek tahmin doğruluğuna erişmiş, bunu sırasıyla SARIMA ve HW toplamsal modeli takip etmiştir

Anahtar Kelimeler

Holt-Winters, SARIMA, Üstel düzeltme, Zaman serileri, Turizm tahmini

Performance Comparison of Holt-Winters and SARIMA Models for Tourism Forecasting in Turkey

Öz

Forecasting the number of tourists coming to Turkey can play a vital role in strategic planning for both private and public sectors. In this study, monthly data of foreigners visiting Turkey were collected between the years 2007 and 2018. The data showed a seasonal behavior with an increasing trend; consequently, two methods were chosen for the study: Holt-Winters HW and Seasonal Autoregressive Integrated Moving Average SARIMA . The objective of the study is to determine the most appropriate forecasting model to achieve a good level of forecasting accuracy. The findings showed that all models provided accurate forecast values according to error measures. However, multiplicative model of HW achieved the highest forecasting accuracy followed by SARIMA and additive HW respectively.

Anahtar Kelimeler

Holt-Winters, SARIMA, Exponential smoothing, Time-series, Tourism forecasting.

Kaynakça

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