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All Journal International Journal of Health, Engineering and Technology Sevaka: Hasil Kegiatan Layanan Masyarakat
Riyan Agus Faisal
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Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Dentistry Education Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Implementation of the Neural Network Algorithm in Monitoring Child Development to Screen for Developmental Disorders at an Early Age Santosa Pohan; Rani Darma Sakti Tanjung; Riyan Agus Faisal; Nur Indah Nasution; Nadya Fitriani; Juni Purwanto
International Journal of Health Engineering and Technology Vol. 4 No. 1 (2025): IJHET May 2025
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v4i1.272

Abstract

This research aims to implement a Neural Network (NN) in monitoring children's development, especially to detect developmental disorders from an early age. The data used includes variables such as Age, Height, and Weight, which have been normalized to have a uniform scale. The modeling process begins with the use of Convolutional Layers to extract important features from numerical data, which are then passed to the ReLU activation layer to introduce non-linearity to the model, enabling the detection of more complex patterns. After that, Max Pooling is carried out to reduce data dimensions and increase computing efficiency. This model was trained using 100 normalized data, and continued with the use of fully connected layers to process further information. In the output layer, a sigmoid activation function is used to generate probability predictions, allowing binary classification (whether a developmental disorder is present or not). Evaluation results show that this model has an accuracy of 85%, which indicates its effectiveness in detecting child developmental disorders based on available data. Although the results are promising, there is still room for improvement, especially in improving the model's accuracy and ability to handle more complex data. Overall, this research shows that Neural Networks can be a useful tool in the early detection of childhood developmental disorders, with potential for broad applications in the fields of children's health and education.
Pemberdayaan Remaja Sebagai Agen Kepemimpinan Kesehatan Masyarakat Berbasis Komunitas Riyan Agus Faisal; Novica Jolyarni; Devi Nur Fitriyana
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 3 No. 3 (2025): Agustus : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v3i3.564

Abstract

Youth empowerment is an effective strategy for improving the quality of community-based public health. As the nation's next generation, adolescents have great potential to become agents of change, including in the health sector. This study aims to develop a model for empowering adolescents as agents of public health leadership at the community level. The method used is a community-based participatory research approach involving adolescents, community leaders, and health workers. The results show that leadership training, health education, and social activities can increase the capacity of adolescents to lead and educate the community about clean and healthy living behaviors. The implementation of these activities also shows increased community participation and changes in health behaviors in the target environment. In conclusion, empowering adolescents as agents of community leadership can be a sustainable strategy for strengthening a public health system based on active participation.
Co-Authors Devi Nur Fitriyana Juni Purwanto Nadya Fitriani novica jolyarni Nur Indah Nasution Santosa Pohan Tanjung, Rani Darma Sakti