Random Forest Algorithm for Toddler Nutritional Status Classification Website
Accurate data processing is essential for classifying toddler nutritional status on a website platform. The Random Forest algorithm is particularly effective in this context due to its ability to manage large datasets and mitigate overfitting. This study leverages Flask as the web framework to ensur...
Saved in:
| Main Authors: | Maylia Fatmawati, Bambang Agus Herlambang, Noora Qotrun Nada |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Politeknik Negeri Batam
2024-11-01
|
| Series: | Journal of Applied Informatics and Computing |
| Subjects: | |
| Online Access: | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/8463 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
THE RELATIONSHIP OF THE NUTRITIONAL STATUS OF PREGNANT WOMEN AND STUNTING IN TODDLER AT THE HUSADA CLINIC, JOMBANG
by: Ike Kristian, et al.
Published: (2023-10-01) -
Socioeconomic Relationship And Feeding Patterns With The Nutritional Status Of Toddlers In The Working Area Of The Amonggedo Health Center, Konawe Regency
by: Ari Nofitasari, et al.
Published: (2024-05-01) -
Correlation of Intestinal Protozoa Infection with the Nutritional Status of Toddlers Aged 12–59 Months in Jember Regency, East Java, Indonesia
by: Rizky Robeth Ardyansyah, et al.
Published: (2024-06-01) -
Maternal Parenting Practices in Feeding and Their Impact on Nutritional Status of Toddlers in Mampang Village, Depok City, West Java
by: Rahmi Nurmadinisia, et al.
Published: (2025-06-01) -
THE EFFECT OF STUNTING EARLY DETECTION (STULYTION) WEBSITE ON THE LEVEL OF KNOWLEDGE OF BALANCED NUTRITION IN MOTHERS AGED 12-59 MONTHS AT KEBONARUM KLATEN HEALTH CENTER
by: Brigita Senanda Septia Firma, et al.
Published: (2025-03-01)