Denetimde Makine Öğreniminin Kullanımına Yönelik Bibliyometrik Bir Analiz
DOI:
https://doi.org/10.63556/tisej.2025.1465Anahtar Kelimeler:
Muhasebe- Denetim- Makine Öğrenmesi- R-Studyo- BibliyometrikÖzet
Bu çalışmanın amacı denetim alanında kullanılan en uygun makine öğrenmesi yöntemlerini belirlemek ve bu yöntemlerin denetim alanına katkılarını ortaya koymaktır. Bu bağlamda bibliyometrik analiz yöntemi kullanılmıştır. Bu analiz kapsamında, Scopus veri tabanından 147, Web of Science veri tabanından ise 99 olmak üzere toplam 246 çalışma incelenmiştir. Verilerin birleştirilmesinin ardından analiz için 160 çalışma seçilmiştir. Bibliyometrik verilerin analizi Biblioshiny yardımıyla R-Studio programında Bibliometrix paketi kullanılarak yapılmıştır. Bulgular, lojistik regresyon ve doğrusal regresyon analizinin 1980'lerden bu yana denetimde yaygın olarak kullanılan makine uygulamaları olmaya devam ettiğini göstermektedir. Ayrıca analizler son yıllarda derin öğrenme, Uzun-Kısa Süreli Bellek, Beetle Antennae Search, Rastgele Orman ve XGBoost gibi ileri uygulamaların daha fazla tercih edildiğini göstermektedir. Bu çalışma, denetim alanında makine öğrenimi üzerine araştırma yapmak için kapsamlı bir yol haritası geliştirmeyi amaçlayan gelecekteki araştırmacılar için değerli içgörüler sunmaktadır. Çalışma ayrıca, denetimin muhasebe disiplini içinde, ancak disiplinler arası bir bakış açısıyla ele alınmasının gerekliliğini vurgulamakta ve bu çerçevede literatüre yeni bakış açıları kazandırmaktadır.
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Telif Hakkı (c) 2025 Üçüncü Sektör Sosyal Ekonomi Dergisi

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