PERBANDINGAN ALGORITMA SVM, KNN, DAN NAÏVE BAYES DALAM KLASIFIKASI PENYAKIT CACAR MONYET

TAMIKA (SEMNASTIK 2024) - Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi [E-ISSN 2828-1276]
2 Februari 2025 oleh
PERBANDINGAN ALGORITMA SVM, KNN, DAN NAÏVE BAYES DALAM KLASIFIKASI PENYAKIT CACAR MONYET
kelvin leonardi

Abstrak


Kemajuan teknologi medis telah memungkinkan penerapan pembelajaran mesin untuk klasifikasi penyakit, termasuk cacar monyet. Cacar monyet adalah penyakit zoonosis yang disebabkan oleh virus cacar monyet dan dapat dideteksi melalui data pasien. Penelitian ini bertujuan untuk membandingkan kinerja algoritma Support Vector Machine (SVM), k-Nearest Neighbors (KNN), dan Naïve Bayes dalam membangun model klasifikasi cacar monyet. Dataset yang digunakan terdiri dari 25.000 rekam medis pasien. Hasil penelitian menunjukkan bahwa model SVM dengan kernel linear mencapai akurasi terbaik dibandingkan dengan KNN dan Naïve Bayes. Temuan ini menunjukkan bahwa model SVM dengan kernel linear sangat efektif dalam mengklasifikasikan cacar monyet, sehingga menawarkan potensi besar untuk aplikasi medis lebih lanjut.

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Kelvin Leonardi Kohsasih

Universitas Potensi Utama

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Citation:

K. L. Kohsasih. "Comparison of SVM, KNN, And Naïve Bayes Algorithms in Monkeypox Disease Classification" TAMIKA, vol. 4, no. 2(Semnastik)(2024),hlm. 168-174.

Publication:
Vol. 4 No. 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
DOI:
https://doi.org/10.46880/tamika.Vol4No2(SEMNASTIK).pp168-174

Copyright:

Copyright (c) Tamika
PERBANDINGAN ALGORITMA SVM, KNN, DAN NAÏVE BAYES DALAM KLASIFIKASI PENYAKIT CACAR MONYET
kelvin leonardi 2 Februari 2025
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