CLASSIFICATION OF STUNTING STATUS IN TODDLERS USING NAIVE BAYES METHOD IN THE CITY OF MADIUN BASED ON WEBSITE
DOI:
https://doi.org/10.33480/techno.v19i2.3337Kata Kunci:
Klasifikasi, Naïve Bayes, Data Mining, Stunting, Python.Abstrak
Stunting pada balita merupakan masalah gizi kronis yang sedang dialami dunia kesehatan. Anak dengan kondisi stunting mengalami kecenderungan penurunan tingkat kecerdasan, gangguan berbicara dan kesulitan dalam menangkap pembelajaran dalam metode yang biasa. Kota Madiun masih menghadapi tantangan dalam permasalahan gizi stunting. Prevalensi angka stunting tahun 2020 sebesar 10,18 persen atau 814 anak dari total 7.996 yang diukur. Penggunaan data mining dapat digunakan dalam berbagai bidang yang berhubungan dengan sekumpulan data yang banyak. Terdapat beberapa teknik pengerjaan data mining dalam pengambilan suatu informasi, diantaranya adalah klasifikasi. Umumnya klasifikasi status stunting menggunakan indeks TB/U atau tinggi badan dibanding usia. Pada penelitian ini, metode yang digunakan adalah metode naive bayes, yakni metode yang digunakan untuk memprediksi berbasis probabilitas, sistem yang dibangun menggunakan bahasa pemrograman python dan flask sebagai framework-nya. Dari hasil pengujian yang dilakukan menunjukkan bahwa metode naive bayes dapat digunakan dalam melakukan klasifikasi terhadap status stunting pada balita. Algoritma Naïve Bayes yang diimplementasikan ini, memiliki performansi nilai rata-rata yaitu akurasi sebesar 58%, precision sebesar 68%, dan recall sebesar 58% dari hasil pengujian confusion matrix dengan 30% data testing dan 70% data training.
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