Work

Implementation Model Forward Chaining for Detection Early Toddler Malnutrition Age 0-59 Month

Year: 2024

Type: article

Abstract: This study focuses on the problem of malnutrition in toddlers in Indonesia, who experience multiple nutritional challenges. Toddler age is a critical period in growth and development, but a lack of nutritional intake can lead to long-term health problems. To overcome this problem, the study proposed the development of an Expert System for Poor Nutrition in Toddlers using the Laravel Framework-based Forward Chaining method. This system will assist health workers in diagnosing malnutrition in toddlers by using anthropometric information such as Body Weight According to Body Length or Height children aged 0-60 months. With variables such as gender, age, weight, and length/height, this system can generate a z-score to determine the nutritional status of toddlers.

Source: Jurnal Aisyah Jurnal Ilmu Kesehatan

DOI: 10.30604/jika.v9i2.2895

Authors: Ferly Ardhy, Abdullah Abdullah, Fadzlan Thoriq

Institution: Aisyah University

Language: English

Topic: Edcuational Technology Systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Zero hunger, Good health and well-being

Open Access status: diamond

OpenAlex ID: W4404800712

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