Prediksi Kemungkinan Penyakit Liver menggunakan Algoritma Klasifikasi Naive Bayes

Abdussomad Abdussomad(1*), Ilham Kurniawan(2), Agung Wibowo(3)

(1) Universitas Bina Sarana Informatika
(2) Universitas Bina Sarana Informatika
(3) Universitas Bina Sarana Informatika
(*) Corresponding Author

Sari


Masalah: Penyakit liver merupakan masalah kesehatan utama bagi jutaan orang di seluruh dunia. Prediksi dan identifikasi dini sangat penting untuk mengambil tindakan yang tepat pada tahap awal penyakit ini.

Tujuan: Penelitian ini bertujuan untuk mengevaluasi kemampuan algoritma klasifikasi Naive Bayes dalam memprediksi penyakit liver berdasarkan fitur klinis yang relevan. Menggunakan dataset yang mencakup informasi medis dari sejumlah pasien, kami mengimplementasikan model klasifikasi Naive Bayes untuk mengidentifikasi pola yang berkaitan dengan kondisi penyakit liver.

Metode: Menerapkan metode pembelajaran mesin dalam memprediksi penyakit liver dapat meningkatkan hasil medis secara signifikan, mengurangi beban kondisi tersebut, dan mendorong praktik perawatan kesehatan yang proaktif dan preventif bagi mereka yang berisiko.

Hasil: Hasil analisis menunjukkan bahwa algoritma Naive Bayes mampu memberikan prediksi yang cukup akurat terhadap status kesehatan liver, dengan tingkat akurasi mencapai 91%. Temuan ini menandakan potensi besar algoritma Naive Bayes sebagai alat bantu dalam diagnosis penyakit liver, memungkinkan identifikasi dini dan penanganan yang tepat untuk pasien yang terkena dampak kondisi ini.

Kesimpulan: Kesimpulan ini menyoroti peran penting teknologi dalam meningkatkan praktik medis melalui prediksi penyakit berbasis data.

Teks Lengkap:

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Referensi


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DOI: http://dx.doi.org/10.31602/tji.v15i3.15288

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