IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK PENENTUAN STATUS KANKER

Ach.  Zubairi; Hermanto Hermanto; Hari  Santoso; Abdus  Samad; Ahmad Homaidi

doi:10.35316/justify.v3i2.6467

Ach. Zubairi Fakultas Syariah dan Ekonomi Islam, Universitas Ibrahimy
Hermanto Hermanto Fakultas Sains dan teknologi, Universitas Ibrahimy
Hari Santoso Fakultas Sains dan teknologi, Universitas Ibrahimy
Abdus Samad Fakultas Sains dan teknologi, Universitas Ibrahimy
Ahmad Homaidi Fakultas Sains dan teknologi, Universitas Ibrahimy

10.35316/justify.v3i2.6467

Abstract

Kanker merupakan tantangan kesehatan global utama dengan tingkat kematian yang signifikan. Penentuan status kanker yang akurat penting untuk diagnosis dan strategi pengobatan yang tepat. Penelitian ini mengeksplorasi algoritma K-Nearest Neighbor (KNN) dalam klasifikasi jenis kanker, dengan fokus pada dataset kanker payudara dari UCI Machine Learning Repository. Metodologi yang digunakan mencakup pengumpulan data, seleksi atribut, pemisahan data menjadi training dan testing, serta implementasi KNN. Hasil menunjukkan bahwa KNN dapat mencapai akurasi 87.61% dalam klasifikasi dengan evaluasi menggunakan metrik seperti presisi, recall, dan F1-score. Investigasi lebih lanjut diperlukan untuk mengoptimalkan nilai K, waktu komputasi, dan penanganan dataset besar untuk penerapan yang lebih efektif dalam onkologi.

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