HARTANA, RISKY DEVANDRA (2024) CLASSIFICATION OF STUNTING NUTRITIONAL STATUS IN TODDLERS USING THE NAIVE BAYES CLASSIFIER METHOD. Tugas Akhir thesis, Informatics.
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Abstract
ABSTRACT Stunting in toddlers represents a prevalent issue of malnutrition in Indonesia, primarily attributed to insufficient intake of essential nutrients. This study aims to develop a classification model for assessing the nutritional status related to stunting in toddlers, utilizing the Naive Bayes Classifier method. The dataset comprises information from 182 toddlers residing in Malebo, Kandangan, Temanggung, and Central Java and includes variables such as nutritional status, child identification number, family income, parental occupation, educational attainment, gender, and age in months. The data were analyzed using the Naive Bayes Classifier to categorize the nutritional status concerning stunting. The findings indicate that this method achieved an accuracy rate of 87.27%, suggesting its effectiveness in identifying toddlers affected by stunting. Consequently, this methodology is anticipated to be employed in future research endeavors to enhance the quality of life for children in Indonesia and mitigate the risk of more severe health issues. Keywords: Stunting, Naive Bayes Classifier, Toddler Nutritional Status, Anthropometry, Indonesia
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 05 Dec 2024 06:18 |
| Last Modified: | 05 Dec 2024 06:18 |
| URI: | http://eprints.uty.ac.id/id/eprint/17104 |
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