ANALYZING THE IMPACT OF THE 2023 GENERAL ELECTIONS ON LAND PRICES USING MACHINE LEARNING: A CASE STUDY IN ÇANAKKALE, TURKEY

dc.contributor.authorDogan, Simge
dc.contributor.authorGenc, Levent
dc.contributor.authorYucebas, Sait Can
dc.contributor.authorYalpir, Sukran
dc.date.accessioned2025-05-29T02:57:21Z
dc.date.available2025-05-29T02:57:21Z
dc.date.issued2025
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractThis study analyses the impact of the general elections to be held on 14 May 2023 on the real estate market in Turkey. The aim of the study is to develop a model to predict land unit prices (Turkish Lira/m2) by analysing land prices, exchange rates and gold values observed before (February-March-April) and after (May-June-July) elections for Ayvac & imath;k, Bayrami & ccedil;, Biga, & Ccedil;an, Eceabat, Ezine, Gelibolu, Lapseki, Merkez and Yenice districts of & Ccedil;anakkale province. Daily fluctuations in foreign exchange and gold values, which are the main economic parameters in the study, were recorded during the election period. The findings of this research, which predicts price movements in the property market using machine learning methods such as regression trees, reveal that unit prices of land generally tend to increase with increases in exchange rates, but in some districts where gold prices increase, the unit price shows a reverse trend. This is attributed to the fact that investors prefer gold as a safer asset in times of economic uncertainty. The results obtained can help investors and buyers to predict future trends in property prices, as well as contribute to the development of economic policies by experts to stabilise fluctuations in investment instruments.
dc.identifier.doi10.36306/konjes.1579931
dc.identifier.issn2667-8055
dc.identifier.issue1
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.36306/konjes.1579931
dc.identifier.urihttps://hdl.handle.net/20.500.12428/30020
dc.identifier.volume13
dc.identifier.wosWOS:001470432500010
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherKonya Teknik Univ
dc.relation.ispartofKonya Journal of Engineering Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250529
dc.subjectElection
dc.subjectSustainabilty Land Price
dc.subjectEconomic Parameters
dc.subjectRegression Tree
dc.subjectMachine Learning
dc.titleANALYZING THE IMPACT OF THE 2023 GENERAL ELECTIONS ON LAND PRICES USING MACHINE LEARNING: A CASE STUDY IN ÇANAKKALE, TURKEY
dc.typeArticle

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