IMPLEMENTATION OF DATA MINING MODELS WITH ALGORITHMS K-NEAREST NEIGHBOR IN MONITORING THE NUTRITIONAL STATUS OF CHILDREN AND STUNTING

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mutammimul -
Sayed Fachrurrazi
Reyhan Achmad Rizal
Mauliza -
Syarkawi -

Abstract

Information systems are needed in the development of children in the developmental period and especially in the world of health. Monitoring of children's nutritional status and stunting is necessary to determine children's weight and meet the criteria for children's nutritional status. Pukesmas Muara Satu, North Aceh District, is an implementing element or assistant to the duties of Poskesdes and Midwives in the Health of children's nutritional status and stunting in Paloh Punti Village, which is one of the agencies under the Ministry of Health. This study aims to monitor the growth and development of children such as measuring weight, height, measured to detect early if unwanted things occur such as malnutrition. The problem in this study is designing and monitoring an Information system for child nutritional status and stunting that is integrated with a web application. The purpose of this study is to find out staff and employees in managing, monitoring and accessing data. So that the data at the puskesmas is recorded in the system, and can quickly determine data on the nutritional status of children and stunting. The results of this study are to be able to find out an information system that is able to reduce problems that occur in managing data on the nutritional status of children and stunting at the Muara Satu Health Center. This system is very important because it can make it easier for staff to record the nutritional status of children and stunting at the Health Center. then the results of the KNN (K-Nearest Neighbor) model classification with the recapitulation of the value of new cases with old cases in the first test section is 0.6944, the second test is 0.6388, the third test is 0.555, the fifth test is 0.6388.

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How to Cite
[1]
mutammimul -, S. . Fachrurrazi, R. A. Rizal, M. -, and S. -, “IMPLEMENTATION OF DATA MINING MODELS WITH ALGORITHMS K-NEAREST NEIGHBOR IN MONITORING THE NUTRITIONAL STATUS OF CHILDREN AND STUNTING”, JUSIKOM PRIMA, vol. 6, no. 2, pp. 11-16, Feb. 2023.
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References

W. R. W. Widianawati, Evina, “Optimalisasi Pengolahan Data Rekam Medis Untuk Meningkatkan Kualitas Kader Posyandu Dan Literasi Kms Pada Ibu Balita.,” VISIKES J. Kesehat. Masy., vol. 18, no. 2, 2020.

M. M. Mutammimul Ula, Ananda Faridhatul Ulva, “Implementasi Machine Learning Dengan Model Case Based Reasoning Dalam Mendiagnosa Gizi Buruk Pada Anak,” J. Inform. Kaputama, vol. 5, no. 2, pp. 333–339, 2021.

M. Ula, Bakhtiar, D. Yulisda, B. Badriana, and A. Bintoro, “APPLICATION OF THE FUZZY TIME SERIES MODEL IN CLOTHING MATERIAL STOCK FORECASTING,” vol. 6, pp. 56–61, 2022, doi: 10.34012/jurnalsisteminformasidanilmukomputer.v6i1.

M. Yahya, “Algoritma K-Means Untuk Klasifikasi Provinsi di Indonesia Berdasarkan Paket Pelayanan Stunting,” PANRITA J. Sci. Technol. Arts, vol. 1, no. 2, pp. 41–46, 2022.

P. Ernawati, Rosmalina, “Effect of the Pregnant Women’S Protein Intake and their Baby Leght At Birth To the Incidence of Stunting Among Childern Aged 12 Months,” Penelit. Gizi dan Makanan, 2013.

A. M. F. Ali I., Kurnia D. A., Pratama M. A., “Klasifikasi Status Stunting Balita Di Desa Slangit Menggunakan Metode K-Nearest Neighbor,” KOPERTIP J. Ilm. Manaj. Inform. dan Komput., vol. 5, no. 3, pp. 35–39, 2022.

M. Mauliza, Mutammimul Ula, Ilham Saputra, Rosya Afdelina, and Muhammad Ikhsan, “Application of Expert System With Forward Chaining Method in Detecting Infectious Diseases in Children,” Sci. Midwifery, vol. 10, no. 4, pp. 2777–2785, Sep. 2022, doi: 10.35335/midwifery.v10i4.714.

J. A. Lestari, Eplia Triwira, “Implementasi Algoritma Naive Bayes Classifier dan K-Nearest Neighbor untuk Klasifiasi Status Gizi Obesitas Anak Disabilitas: Implementation Naive Bayes Classifier Algorithm and K-Nearest Neighbor for Obesity Nutritional Status of Children with Disabilitie,” SENTIMAS Semin. Nas. Penelit. dan Pengabdi. Masy., vol. 1, no. 1, 2022.

A. H. G, Sistem Informasi Pendataan Kelahiran dan Timbuh Kembang Bayi Berbasis Web. 2016.

F. Yolanda I., “Penerapan Data Mining Untuk Prediksi Penjualan Produk Roti Terlaris Pada PT.Nippon Indosari Corpindo Tbk Menggunakan Metode K-Nearest Neighbor,” J. Ilmu Komput. Dan Sist. Inf., vol. 3, no. 1.1, pp. 9–15, 2021, doi: https://doi.org/10.9767/jikomsi.v3i1.1.83.

M. Ula, A. Pratama, Y. Asbar, W. Fuadi, R. Fajri, and R. Hardi, “A New Model of The Student Attendance Monitoring System Using RFID Technology,” J. Phys. Conf. Ser., vol. 1807, p. 12026, 2021, doi: 10.1088/1742-6596/1807/1/012026.

M. U. Fitria, Rahma, Desvina Yulisda, “Data Mining Classification Algorithms For Diabetes Dataset Using Weka Tool,” J. Sist. Inf., vol. 2, no. 1, 2021.

H. Andrianof, “Sistem Pakar Stunting Pada Balita Menggunakan Metode Forward Channing & Naive Bayes,” J. Sains Inform. Terap., vol. 1, no. 2, pp. 115–119, 2022.