Bu çalışmada okullarda görev alacak yarı zamanlı öğretmenlere yönelik verinin çeşitli sınıflandırma algoritmaları kullanılarak, yapılan atamaların başarı ölçümünü gözlemlemek ve yapılan işlemin yapay zeka destekli sınıflandırma algoritmaları ile yürütülmesi durumuna yönelik analizi gerçekleştirilmiştir. Çalışmada web tabanlı bir uygulama üzerinden yapılan başvurular ile elde edilen verilerin, gereksinimler doğrultusunda yapılan atama ölçütlerine yönelik başarımı ölçülmüştür. Bunun için 3053 adayın başvurduğu sistemden gereksinim doğrultusundaki 894 adayın atanmasına yönelik öznitelikler üzerinde çalışılmıştır. Altı farklı sınıflandırıcı üzerinde yapılan çalışmada 0,71 Doğruluk ve 0,77 F-ölçüsü ile en iyi sonucu Rassal Orman Sınıflandırıcısı vermiştir. Yapılan bu çalışma ile atama ölçünlerinin ağırlıklarına göre bu çalışmanın uygun sınıflandırıcılar ile yürütülmesi ve bu alanda kullanılabileceği gösterilmiştir.
In this study, the data for part-time teachers who will work in schools were analyzed using various classification algorithms to observe the success measurement of the assignments and automate the process with artificial intelligence-supported classification algorithms. In the study, the performance of the data
obtained through the applications made through a web-based application, for the assignment criteria made in line with the needs, was measured. For this, the attributes for the appointment of 894 candidates in line with the needs from the system applied by 3053 candidates were studied. In the study conducted on six different classifiers, the Random Forest Classifier gave the best result with an accuracy value of 0.71 and an f-score of 0.77. With this study, it has been shown that this study can be automated with appropriate classifiers and used in this field according to the weights of the assignment criteria.
Primary Language | Turkish |
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Subjects | Engineering |
Journal Section | Makaleler(Araştırma) |
Authors | |
Early Pub Date | December 3, 2022 |
Publication Date | December 15, 2022 |
Published in Issue | Year 2022 Volume: 15 Issue: 2 |
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