<![CDATA[Primary education plays a strategic role in shaping students’ character and competencies from an early age. However, many schools face challenges in managing student development data, particularly in aspects related to character, which are often subjective and difficult to quantify systematically. This study aims to develop an artificial intelligence (AI)-based student data system integrated with natural language processing (NLP) to support teachers in analyzing student character and monitoring individual growth. The research employed a Research and Development (R&D) approach consisting of four stages: needs analysis, system design, web application implementation, and system evaluation. The system integrates NLP, TF-IDF, and BERT for feature extraction, character classification using decision tree and ensemble learning, and ChatGPT API to generate character summaries and learning recommendations based on teachers’ observational texts. The application was developed as a web-based platform under the domain aidata.itananda.sch.id and was tested on 48 students at SD IT Ananda Empat Lawang. Evaluation results showed that the system achieved 88% classification accuracy and provided data visualizations such as character distribution graphs and a confusion matrix. This system is expected to improve teachers’ efficiency in understanding student character and designing more adaptive and data-driven learning strategies. The study supports digital transformation in primary education through the integration of AI into school information systems.]]>
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