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All Journal UNP Journal of Statistics and Data Science
Yunistika Ilanda
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Perbandingan Metode Prediksi Laju Galat dalam Pemodelan Klasifikasi Algoritma C4.5 untuk Data Tidak Seimbang Yunistika Ilanda; Dodi Vionanda; Yenni Kurniawati; Dina Fitria
UNP Journal of Statistics and Data Science Vol. 1 No. 4 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol1-iss4/89

Abstract

Classification modeling can be formed using the C4.5 algorithm. The model formed by the C4.5 algorithm needs to be seen for its prediction accuracy using the error rate prediction method. Imbalanced data causes an increase in the classification error of the C4.5 algorithm because the prediction results do not represent the entire data and worsen the performance of the error rate prediction method. Meanwhile, the case of data with different correlations is carried out to find out whether different correlations affect the performance of the error rate prediction method. The purpose of the research is to find out the most suitable error rate prediction method applied to the C4.5 algorithm in the case of imbalanced data and the influence of different correlations. The results show that the K-Fold CV method is the most suitable prediction method applied to the C4.5 algorithm for imbalanced data cases compared to the HO and LOOCV methods. In addition, high correlation can worsen the performance of error rate prediction methods.
Co-Authors Dina Fitria Dodi Vionanda Yenni Kurniawati