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All Journal International Journal of Information Technology and Computer Science Applications (IJITCSA) Jurnal Riset Informatika dan Teknologi Informasi (JRITI)
Dr. Tb. Ai Munandar, S.Kom., MT
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Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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Clustering of Child Nutrition Status using Hierarchical Agglomerative Clustering Algorithm in Bekasi City Ozzi ardhiyanto; Muhammad Salam Asyidqi; Ajif Yunizar Pratama Yusuf, S.Si, M.Eng; Dr. Tb. Ai Munandar, S.Kom., MT
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 3 (2023): September - December 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v1i3.42

Abstract

Clustering infant nutrition based on weight, height, and age is a data analysis method used to group infant nutritional status based on these characteristics. The research on clustering infant nutrition aims to analyze whether there are still many infants in the area with insufficient or excessive nutrition, and to identify groups of infants requiring special attention regarding their nutritional intake. In the analysis of infant nutrition clustering, data on weight, height, and age of infants are collected and then grouped based on similarities in body height and weight at certain ages. The method used in this research is hierarchical clustering, which can help in grouping the data. Clustering analysis can help understand how infants' feeding patterns vary based on their weight, height, and age. The results of research on clustering infant nutrition based on weight, height, and age can provide valuable insights for nutrition experts, pediatricians, and community health workers in developing appropriate intervention programs to improve infant feeding patterns and meet their nutritional needs. Additionally, the results of clustering infant nutrition can also be used to identify groups of infants requiring special attention regarding their nutritional needs, thus minimizing the risk of malnutrition and unhealthy growth in infants.
Clustering of Child Nutrition Status using Hierarchical Agglomerative Clustering Algorithm in Bekasi City ardhiyanto, ozzi; Ajif Yunizar Pratama Yusuf, S.Si, M.Eng; Salam Asyidqi, Muhammad; Dr. Tb. Ai Munandar, S.Kom., MT
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.41

Abstract

Clustering infant nutrition based on weight, height, and age is a data analysis method used to group infant nutritional status based on these characteristics. The research on clustering infant nutrition aims to analyze whether there are still many infants in the area with insufficient or excessive nutrition, and to identify groups of infants requiring special attention regarding their nutritional intake. In the analysis of infant nutrition clustering, data on weight, height, and age of infants are collected and then grouped based on similarities in body height and weight at certain ages. The method used in this research is hierarchical clustering, which can help in grouping the data. Clustering analysis can help understand how infants' feeding patterns vary based on their weight, height, and age. The results of research on clustering infant nutrition based on weight, height, and age can provide valuable insights for nutrition experts, pediatricians, and community health workers in developing appropriate intervention programs to improve infant feeding patterns and meet their nutritional needs. Additionally, the results of clustering infant nutrition can also be used to identify groups of infants requiring special attention regarding their nutritional needs, thus minimizing the risk of malnutrition and unhealthy growth in infants.
Co-Authors Ajif Yunizar Pratama Yusuf Ardhiyanto, Ozzi Muhammad Salam Asyidqi Ozzi ardhiyanto Salam Asyidqi, Muhammad