This is a synthetic demo. Every student, grade, course, financial figure and retention number is generated locally for demonstration. It is not official Silliman University data and the demo is not affiliated with or endorsed by the university.
How the numbers were built
- A seeded generator creates an 8,200-student snapshot for AY 2026–27, 1st Semester, across 13 colleges and a Silliman-like program mix.
- Risk is a transparent composite of GWA, attendance, LMS engagement, failed courses, financial holds and transition factors. It is designed to show how an early-warning model would work, not to label real students.
- Historical enrollment, retention, graduation, tuition, aid, faculty, sections and capacity are calibrated to plausible university ranges and then charted consistently.
- GWA uses the Philippine 1.0–4.0 scale: 1.0 is best and 4.0 is lowest. The at-risk threshold shown is 2.75.
- Financial values are in Philippine pesos. Tuition and aid are shown in millions; collection and net tuition are modelled, not audited.
- The retention scenario is an illustrative calculation, not a forecast. It holds tuition and yield constant and ignores capacity constraints.
What a real deployment would need
- Consent-based student information system, LMS, attendance and advising data.
- Data governance, access controls, audit logs and FERPA/Data Privacy Act alignment.
- Adviser feedback loops, intervention tracking and model monitoring for bias and drift.
Built as an independent alumni portfolio demo. Brand colours follow the public Silliman University website palette; no official marks or logos are used.