Implementasi Sistem Informasi Rapor Online di SMA Kristen Elim Makassar
Bibliographic record
Abstract
Pendidikan sangatlah penting bagi masa depan generasi muda Indonesia saat ini. Untuk melahirkan generasi emas Indonesia yang lebih baik, para tenaga pengajar harus memiliki sebuah tolak ukur nilai siswa dalam melihat perkembangan nilai dan keaktifan siswa yang di sebut Rapor. Saat ini penerapan teknologi sebagai media pengelolaan nilai rapor oleh guru yang masih kurang efektif dan tidak efesien dari segi waktu. Tujuan dari pelatihan ini adalah membuat suatu aplikasi rapor online berbasis website untuk mempermudah guru dalam pengelolaan nilai siswa dan mempermudah orang tua dalam memonitoring nilai anak-anak mereka. Hasil yang didapatkan dari pengabdian ini adalah pelatihan penggunaan aplikasi rapor online sudah berjalan dengan baik dan dapat diimplementasikan oleh para guru di SMA Kristem Elim Makassar.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.015 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".