PENGEMBANGAN SISTEM PELACAKAN ALUMNI (TRACER STUDY) MENGGUNAKAN METODE PROTOTIPE BERBASIS WEBSITE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pelacakan alumni (tracer study) menjadi salah satu kegiatan yang sangat penting penting untuk dilakukan secara berkala dan konsisten. Pelacakan alumni sebenarnya merupakan salah satu bagian dari pengembangan universitas atau perguruan tinggi yang berkelanjutan. Hasil pelacakan alumni yang baik akan menghasilkan inputan yang baik pula pada universitas khususnya program studi untuk mengembangkan kurikulum dan model pembelajarannya. Sistem pelacakan alumni dibangun berbasis website dengan metode pengembangan sistem prototipe. Pengembangan sistem dimulai dengan pengumpulan data pada objek dan pengguna melalui metode wawancara dan observasi. Setelah itu dilakukan analisa sistem menggunakan metode PIECES dan dilanjutkan dengan perancangan sistem menggunakan metode Unified Modelling Language (UML). Penelitian ini menghasilkan model awal sistem pelacakan alumni yang kedepannya akan terus dikembangkan sesuai dengan perkembangan peraturan dan kebutuhan penggunanya.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it