APLIKASI PREDIKSI STATUS GIZI BALITA BERBASIS WEB MENGGUNAKAN METODE K-NEAREST NEIGHBOR

Authors

  • Dara Atria Ferliandini Program Studi Teknik Informatika, Universitas Sangga Buana
  • Slamet Risnanto Program Studi Teknik Informatika, Universitas Sangga Buana

DOI:

https://doi.org/10.32897/sobat.2023.5.0.3136

Abstract

The nutritional status of children under five is an important parameter in monitoring and caring for children's health, and this research aims to provide a reliable and efficient tool for stakeholders, including health workers and parents. The K-NN method was chosen as the basis for prediction because of its ability to classify nutritional status by comparing the similarity of new toddler data with existing data in the dataset. This application allows users to enter data such as the age, weight, height and gender of the toddler. Using the K-NN algorithm, this application automatically calculates the distance between the toddler to be predicted and the toddlers in the dataset that are most similar to it. Application testing results show a very satisfactory accuracy level of 91.94%. This shows that this application can provide predictions of the nutritional status of toddlers with a high level of confidence, potentially enabling early detection of nutritional problems and timely intervention.

References

O. Penerima, A. Hamengku, and B. Ix, “Pengembangan Teknologi Kesehatan Untuk Menjawab Tantangan Dan Kebutuhan Masa Depan Demi Kemandirian Bangsa,” 2009.

“Penerapan Metode K-Nearest Neighbor (Knn) Untuk Menentukan Status Gizi Balita.”

H. Saleh, M. Faisal, And R. I. Musa, “Klasifikasi Status Gizi Balita Menggunakan Metode K-Nearest Neighbor,” Vol. 4, No. 2, 2019.

A. M. Argina, “Indonesian Journal Of Data And Science Penerapan Metode Klasifikasi K-Nearest Neigbor Pada Dataset Penderita Penyakit Diabetes,” Vol. 1, No. 2, Pp. 29–33, 2020.

M. M. Baharuddin, H. Azis, And T. Hasanuddin, “Analisis Performa Metode K-Nearest Neighbor Untuk Identifikasi Jenis Kaca,” Ilkom Jurnal Ilmiah, Vol. 11, No. 3, Pp. 269–274, Dec. 2019, Doi: 10.33096/Ilkom.V11i3.489.269-274.

T. Rismawan, A. Wiedha Irawan, W. Prabowo, And S. Kusumadewi, “Sistem Pendukung Keputusan Berbasis Pocket Pc Sebagai Penentu Status Gizi Menggunakan Metode Knn (K-Nearest Neighbor),” Vol. 13, No. 2, Pp. 18–23, 2008.

W. Yustanti, “Algoritma K-Nearest Neighbour Untuk Memprediksi Harga Jual Tanah,” 2012.

B. Yulia, L. Fahik, B. S. Djahi, N. D. Rumlaklak, and J. I. Komputer, “Data Mining Untuk Klasifikasi Status Gizi Desa Di Kabupaten Malaka Menggunakan Metode K-Nearest Neighbor,” J-ICON, vol. 6, no. 1, pp. 1–7, 2018.

R. Shafira and A. Pambudi, “Penilaian Status Gizi Balita Menggunakan Metode K-Nearest Neighbor,” 2023. (Online). Available: https://ojs.uniska-bjm.ac.id/index.php/JIT

, S. Oleh, “Hubungan Indeks Masa Tubuh Terhadap Kadar Hemoglobin Sebagai Penanda Anemia Pada Balita Stunting Di Kecamatan Gunung Sugih Kabupaten Lampung Tengah,” 2019.

Downloads

Published

2023-12-09

Issue

Section

Articles