<![CDATA[Monitoring adolescent faith development requires an objective and data-driven approach, whereas existing practices remain largely manual, subjective, and weakly documented. This study proposes a web-based expert system as a decision support tool for classifying levels of adolescent faith development. The novelty of this research lies in the integration of a rule-based inference engine using forward chaining with a structured, indicator-driven assessment framework. The system was developed using a structured software engineering approach, including UML-based functional modeling and an Entity Relationship Diagram (ERD) for database design. The expert system processes assessment data derived from four validated indicators: prayer practice, participation in communal activities, social attitudes, and faith reflection. Data were collected from 30 respondents through a web-based assessment module and analyzed using expert-defined inference rules. The classification results indicate that 33.3% of respondents were categorized as having good faith development, 46.7% moderate, and 20.0% low. Functional testing using black-box methods confirmed that all system features operated according to specifications, while expert validation confirmed the relevance and consistency of indicators and inference rules. These findings demonstrate that the proposed system produces measurable and consistent classification outcomes, contributing to the application of expert systems and web-based decision support technologies for objective adolescent development monitoring.]]>
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