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Transformasi Pemantauan Gizi Anak: Implementasi Aplikasi Website di PKD Desa Karangkemojing Hellyana, Corie Mei; Fadlilah, Nuzul Imam; Saifudin, Saifudin; Widayanto, Aprih
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 15 No 1 (2025): Juli 2025
Publisher : LPPM UNINUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30999/jpkm.v15i2.3362

Abstract

Children's nutritional health is a crucial factor for their growth and development. Regular monitoring of nutrition is essential for detecting and preventing nutritional issues. This study aims to develop a web-based application for monitoring children's nutrition at the Village Health Center (PKD) in Karangkemojing Village. The methodology employed is the System Development Life Cycle (SDLC) approach, involving analysis, design, implementation, and evaluation. This web-based application allows health workers and parents to monitor children's nutritional status regularly through data on weight, height, and other nutrition indicators. It is expected that the use of this application will enhance the efficiency of posyandu cadres in monitoring children's nutrition. Additionally, the application facilitates access to nutritional information for health workers and parents while supporting decision-making regarding nutritional interventions. The utilization of this application is anticipated to serve as a model for other regions in improving the quality of children's health services at the village level.
Transformasi Pemantauan Gizi Anak: Implementasi Aplikasi Website di PKD Desa Karangkemojing Hellyana, Corie Mei; Fadlilah, Nuzul Imam; Saifudin, Saifudin; Widayanto, Aprih
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 15 No 1 (2025): Juli 2025
Publisher : LPPM UNINUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30999/jpkm.v15i2.3362

Abstract

Children's nutritional health is a crucial factor for their growth and development. Regular monitoring of nutrition is essential for detecting and preventing nutritional issues. This study aims to develop a web-based application for monitoring children's nutrition at the Village Health Center (PKD) in Karangkemojing Village. The methodology employed is the System Development Life Cycle (SDLC) approach, involving analysis, design, implementation, and evaluation. This web-based application allows health workers and parents to monitor children's nutritional status regularly through data on weight, height, and other nutrition indicators. It is expected that the use of this application will enhance the efficiency of posyandu cadres in monitoring children's nutrition. Additionally, the application facilitates access to nutritional information for health workers and parents while supporting decision-making regarding nutritional interventions. The utilization of this application is anticipated to serve as a model for other regions in improving the quality of children's health services at the village level.
Penerapan Algoritma Decision Tree Dengan Optimasi Parameter Dalam Memprediksi Reaksi Autoimun Akibat Obat saifudin; Fadlilah, Nuzul Imam; Nouvel, Ahmad; Sunanto, Sunanto
Informatics and Computer Engineering Journal Vol 5 No 2 (2025): Periode Agustus 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/5bjr6g76

Abstract

In the latest developments in medical technology, machine learning, especially the application of the Decision Tree algorithm, is becoming an increasingly popular approach for large-scale health data analysis. Decision Tree is known for its ability to identify hidden patterns in clinical data with interpretation that is easy for medical professionals to understand. Through the process of parameter optimization, the accuracy of the model can be significantly improved, allowing for more precise predictions of possible autoimmune reactions due to the use of certain drugs. The use of Decision Tree-based predictive models with optimized parameters not only strengthens clinical decision-making, but also paves the way for more personalized and precise treatment practices. Parameter optimization is used for the execution of all parameter variations that are set through its subprocesses. The final result recorded an optimal predictive performance of 77.50% with 98.28% more precision for the "true=0" class compared to the "true=1" class.