<![CDATA[When software is developed, thorough functional validation is essential to ensure that applications operate according to design specifications and user expectations. Inadequate data validation can lead to inaccurate database records, causing prediction models to return unreliable forecasts that negatively affect stakeholders. This paper presents a functional verification of an Indonesian livestock population prediction web platform using the Equivalence Partitioning (EP) technique within a Black Box Testing framework. Rather than focusing solely on output validation, this study formalizes input domains by partitioning them into valid and invalid equivalence classes across five core application modules: Authentication, Population Data Management, Predictive Analytics Execution, News Content Administration, and Interactive Mapping. To evaluate testing quality quantitatively, a Test Effectiveness Metric based on the ratio of successfully executed valid test cases to total designed partitions was introduced, achieving a functional effectiveness score of 100% across all 9 designed test cases. The empirical findings confirm that the system correctly enforces input constraints and error-handling logic, providing a robust web application for agricultural planning.]]>
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