Perbandingan Kinerja Algoritma Klasifikasi Naive Bayes, k-Nearest Neighbor dan Logistic Regression pada Dataset Multiclass

WR Wahyudi, SA Adriko, MI Firdaust, MHA Harits, Dian Puspita Hapsari

Abstract


Penelitian ini membandingkan kinerja tiga algoritma klasifikasi: Naive Bayes, k- Nearest Neighbor, dan Logistic Regression pada dataset multiclass. Kinerja masing-masing algoritma dievaluasi menggunakan metrik seperti akurasi, presisi, recall, dan F1-skor. Hasil penelitian menunjukkan bahwa kinerja ketiga algoritma tersebut variatif tergantung pada dataset spesifik yang digunakan. Secara keseluruhan, algoritma regresi logistik yang memiliki kinerja terbaik, diikuti oleh k-Nearest Neighbor dan Naive Bayes. Hasil penelitian ini memberikan wawasan yang bermanfaat bagi para peneliti dan praktisi yang ingin memilih algoritma yang sesuai untuk masalah klasifikasi multiclass.


Keywords


Algoritma Klasifikasi, Naive Bayes, k-Nearest Neighbour, Regresi Logistik, Multikelas.

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DOI: https://doi.org/10.31284/p.snestik.2023.4157

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