KLASIFIKASI STATUS GIZI BALITA MENGGUNAKAN NAÏVE BAYES CLASSIFICATION DI KELURAHAN PADASUKA CIOMAS BOGOR
DOI:
https://doi.org/10.31848/justise.v3i1.4265Abstract
Life is characterized by symptoms of growth and development. The health status of each individual is different. In this case, one of the efforts to improve health status is to improve nutritional status. Nutritional status is a state of the body related to food consumption patterns and the use of nutrients that are tailored to the body's needs. Improving nutritional status is useful for increasing body resistance and making normal growth. In actualizing the daily nutritional status of children under five at the posyandu, it is usually obtained through anthropometric measurements, namely by using the BW/U index or body weight compared to age to determine nutritional status.
However, in anthropometric measurements, it was found that there was confusion in the determination of nutritional quality, so that in order to get accurate results, a data mining method was needed, namely the Naive Bayes Classification (NBC) Algorithm which would be implemented in the study.
This research is expected to help posyandu cadres in Padasuka sub-district, Ciomas sub-district, Bogor district in determining the nutritional status of toddlers better and more accurately.
References
R. Hariyanto, M. Z. Sarwani dan Y. N. Aprilia, “Prediction of Stunting Nutritional Status in Toddlers Using Naïve Bayes Classifier Algorithm,” JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), vol. 10, no. 2, pp. 1111-1117, 2025.
W. C. Wahyudin, F. M. Hana dan A. Prihandono, “PREDIKSI STUNTING PADA BALITA DI RUMAH SAKIT KOTA SEMARANG MENGGUNAKAN NAIVE BAYES,” JURNAL ILMU KOMPUTER DAN MATEMATIKA, vol. 4, no. 1, pp. 32 - 36, 2023.
S. Taufiq, “Klasifikasi Status Gizi Balita Menggunakan Algoritma Naive Bayes Berdasarkan Pengukuran Antropometri,” Jurnal Ilmu Pengetahuan dan Teknologi (IPTEK), vol. 9, no. 1, pp. 1-5, 2025.
E. R. Arumi, S. A. Subrata dan A. Rahmawati, “Implementation of Naïve bayes Method for Predictor Prevalence Level for Malnutrition Toddlers in Magelang City,” Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), vol. 7, no. 2, pp. 201 - 207, 2023.
N. Chasanah, A. D. Indriyanti dan A. Faizah, “Sistem Penentuan Status Gizi Balita Menggunakan Metode Naive Bayes Classifier (Studi Kasus Posyandu Anggrek Putih Seblak Desa Kwaron),” Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi, vol. 6, no. 2, pp. 1-8, 2022.
R. A. Subhan, A. Asriyanik dan F. F. A. Zahra, “KLASIFIKASI STATUS GIZI BALITA BERDASARKAN TINGGI BADAN DAN BERAT BADAN MENGGUNAKAN METODE NAÏVE BAYES DI PUSKESMAS LIMUSNUNGGAL,” Synergy : Jurnal Ilmiah Multidisiplin, vol. 1, no. 4, p. 217–223, 2024.
M. I. Kamil dan A. P. Wibowo, “Implementation of the Naive Bayes Classifier Algorithm for Classifying Toddler Nutritional Status,” Journal of Applied Informatics and Computing, vol. 8, no. 2, p. 421–427, 2024.
F. Febriansyah, “Implementasi Metode Naive Bayes untuk Klasifikasi Kondisi Gizi Balita,” Jurnal Informatika Universitas Pamulang, vol. 9, no. 2, pp. 61-70, 2024.
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