Wildan Tisna Surya
Universitas Pendidikan Indonesia

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Kids Trackr: An AI-Powered Mobile-Based Information System for Monitoring Elementary School Child Development Muhammad Fajar Jati Permana; Wildan Tisna Surya; Destya Aulia Nurul Hutami; Munawir
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 8 No. 2 (2026): September
Publisher : Universitas Wahid Hasyim

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Abstract

Kids Trackr is a mobile-based information system designed to facilitate the monitoring of primary school children's development in real-time and efficiently. This system integrates Artificial Intelligence (AI) technology through the use of Natural Language Processing (NLP) for chatbot features and Artificial Neural Network (ANN) for child development analysis based on academic data. Using the Agile software development approach, this application is built iteratively and adaptively to user needs, including features for lesson schedules, student attendance, child skills assessment, two-way communication between teachers and parents, and graph-based progress reports. The validation process was conducted through functionality testing and user trials involving teachers, parents, and students at SD Laboratorium Percontohan UPI Cibiru. The test results showed a high level of user satisfaction, with 87.3% of respondents stating the application was easy or very easy to use, 90% stating the application was interactive, and 83.3% stating the application was useful in monitoring children's development. In addition, the ANN algorithm is proven to be able to provide accurate predictive analysis of student learning outcomes. By combining AI technology and user-oriented design principles, Kids Trackr has great potential as an integrated solution in increasing parental involvement, teacher work efficiency, and accuracy of student development reporting at the primary school level.