Implementasi Algoritma K-Nearest Neighbors untuk Rekomendasi Diet Tinggi Serat dalam Mencegah Penyakit Jantung

Maria Anjelina Domu Tukan; Alfian Nara Weking; Dominikus Boli Watomakin

doi:10.31004/riggs.v4i3.2099

Authors

Maria Anjelina Domu Tukan Institut Keguruan dan Teknologi Larantuka
Alfian Nara Weking Institut Keguruan dan Teknologi Larantuka
Dominikus Boli Watomakin Institut Keguruan dan Teknologi Larantuka

DOI:

https://doi.org/10.31004/riggs.v4i3.2099

Keywords:

Penyakit Jantung, Diet Tinggi Serat, K-Nearest Neighbors

Abstract

Penyakit jantung merupakan salah satu ancaman kesehatan utama di era modern dan menjadi penyebab kematian tertinggi di seluruh dunia. Jumlah kematian akibat penyakit jantung mencapai 17,9 juta jiwa secara global. Di Indonesia, angka kematian akibat penyakit jantung terus meningkat dari tahun ke tahun. Tercatat sebanyak 15 dari setiap 1.000 orang, atau sekitar 2.784.064 jiwa di Indonesia, menderita penyakit jantung. Untuk mencegah tingginya angka kematian akibat penyakit jantung, diperlukan upaya pencegahan dini guna mengurangi risiko terjadinya penyakit tersebut. Tujuan dari penelitian ini adalah untuk mengevaluasi efektivitas algoritma K-Nearest Neighbor (K-NN) dalam menganalisis data pola makan tinggi serat guna mencegah penyakit jantung. Penelitian ini juga bertujuan untuk mengidentifikasi pola konsumsi serat yang optimal bagi kesehatan jantung, memberikan rekomendasi gaya hidup sehat berbasis data, serta mengembangkan model prediksi yang akurat dan efisien. Algoritma K-Nearest Neighbor (K-NN) merupakan pendekatan yang sederhana dan mudah diimplementasikan. Metode ini efektif digunakan pada dataset yang memiliki banyak atribut serta mampu menangani permasalahan klasifikasi atau regresi dengan lebih dari dua kelas tanpa memerlukan modifikasi besar. Hasil penelitian menunjukkan bahwa algoritma K-NN sangat efektif dalam merekomendasikan makanan, dengan prediksi model menghasilkan akurasi sebesar 93%.

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