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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Seminar Nasional Informatika (SEMNASIF) Jurnal Teknologi dan Sistem Komputer Knowledge Engineering and Data Science JIKO (Jurnal Informatika dan Komputer) Jurnal TAM (Technology Acceptance Model) ILKOM Jurnal Ilmiah IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal E-Komtek JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal of Informatics and Communication Technology (JICT) Journal of Engineering, Electrical and Informatics (JEEI) Konstelasi: Konvergensi Teknologi dan Sistem Informasi Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Scientific Research, Education, and Technology SmartComp Journal of Technology Informatics and Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi The Indonesian Journal of Computer Science Journal of Informatics and Communication Technology (JICT) Jurnal TAM (Technology Acceptance Model) Jurnal Abdi Rakyat Journal of Engineering, Electrical and Informatics
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Journal : Journal of Technology Informatics and Engineering

Nutritional Status Classification Of Stunting In Toddlers Using Naive Bayes Classifier Method Risky Devandra Hartana; Enny Itje Sela
Journal of Technology Informatics and Engineering Vol 3 No 1 (2024): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i1.154

Abstract

Stunting in toddlers is one of the prevalent issues of malnutrition in Indonesia. The causes of Stunting are diverse, and one contributing factor is the insufficient nutritional intake required for toddlers. The categorization of Stunting nutritional status in toddlers is crucial to identify those experiencing Stunting, enabling appropriate interventions to prevent more serious health problems in the future. This research aims to develop a classification model for short nutritional status in toddlers using the Naive Bayes Classifier method. The data utilized in this study originate from anthropometric measurements of toddlers in the Malebo area, Kandangan, Temanggung, Central Java. The anthropometric data include weight, height, and age of the toddlers. This data is then processed using the Naive Bayes Classifier method to classify the nutritional status of Stunting in toddlers. The results of this research are expected to assist in identifying toddlers experiencing Stunting, facilitating appropriate interventions to prevent more serious health issues in the future. Additionally, the Naive Bayes Classifier method employed can be applied in similar studies to enhance the quality of life, especially for children in Indonesia, particularly in the Malebo area, Kandangan, Temanggung, Central Java.
Nutritional Status Classification Of Stunting In Toddlers Using Naive Bayes Classifier Method Risky Devandra Hartana; Enny Itje Sela
Journal of Technology Informatics and Engineering Vol. 3 No. 1 (2024): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i1.154

Abstract

Stunting in toddlers is one of the prevalent issues of malnutrition in Indonesia. The causes of Stunting are diverse, and one contributing factor is the insufficient nutritional intake required for toddlers. The categorization of Stunting nutritional status in toddlers is crucial to identify those experiencing Stunting, enabling appropriate interventions to prevent more serious health problems in the future. This research aims to develop a classification model for short nutritional status in toddlers using the Naive Bayes Classifier method. The data utilized in this study originate from anthropometric measurements of toddlers in the Malebo area, Kandangan, Temanggung, Central Java. The anthropometric data include weight, height, and age of the toddlers. This data is then processed using the Naive Bayes Classifier method to classify the nutritional status of Stunting in toddlers. The results of this research are expected to assist in identifying toddlers experiencing Stunting, facilitating appropriate interventions to prevent more serious health issues in the future. Additionally, the Naive Bayes Classifier method employed can be applied in similar studies to enhance the quality of life, especially for children in Indonesia, particularly in the Malebo area, Kandangan, Temanggung, Central Java.