• Ana Sayfa

Kahramanmaraş depremi sonrası konut fiyatlarındaki değişim trendinin makine öğrenimine göre belirlenmesi: Gaziantep örneği

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Çanakkale Onsekiz Mart Üniversitesi, Lisansüstü Eğitim Enstitüsü, Türkiye

Tezin Onay Tarihi: 2025

Tezin Dili: Türkçe

Öğrenci: METİN UŞAKLI

Danışman: Levent Genç

Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu

Özet:

Natural disasters are events that change the life course of people and cause many loss of life and property, and their effects are seen for a long time. Especially earthquakes have many negative socio-economic effects. Turkey has experienced many devastating earthquakes due to its geographical location. On February 6, 2023, after the Kahramanmaraş earthquake, which is called "the biggest disaster of 80 years" in Turkey, it is important to examine the fluctuations in housing prices and to determine the effects of structural features on housing prices for the future of the real estate sector in the region. In this context, by using Machine Learning (ML) methods, the change in the prices of houses for sale obtained from the central districts of Gaziantep in the three-month periods (January, February and March) before (2022) and after (2023) the earthquake was analyzed. According to the results of the study, it was found that the demand for security and new housing emerged after the earthquake, and the effects of housing type and façade on house prices decreased. Moreover, structural characteristics such as housing area, district, building age and number of storeys have become critical, and households prefer smaller but safer houses. In price forecasting models, the performance of linear models decreased after the earthquake, while the XGBoost model was the best model to explain the variability. This study shows that the Kahramanmaraş earthquakes have a critical importance for understanding the dynamics of the housing market in Gaziantep province, which stands out in the region due to its diversity in different economic activities such as industry, tourism and agriculture, and for planning the future of the region. Accurate determination of housing prices enables local governments to develop sustainable policies in post-earthquake reconstruction and development processes, while helping individuals to shape their housing preferences.