Employee Construct of Work-Values among University Support-Staff
Bibliographic record
Abstract
Membaca Al-Qur’an memerlukan ketelitian dalam menerapkan kaidah agar terhindar dari kesalahan yang dapat merubah makna. Oleh karena itu, ustadzah harus memiliki strategi pembelajaran yang efektif untuk mengatasi tantangan yang dihadapi santri dalam membaca Al-Qur’an. Penelitian ini bertujuan untuk mendeskripsikan strategi yang digunakan ustadzah dalam menangani kesulitan belajar membaca Al-Qur’an di Pondok Pesantren Tahfidzul Qur’an Al-Hikmah. Metode yang digunakan adalah pendekatan kualitatif dengan jenis penelitian lapangan (field research). Teknik pengumpulan data terdiri dari observasi, wawancara, dan dokumentasi. Analisis data dilakukan melalui tahapan reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa strategi ustadzah memiliki dampak signifikan terhadap kelancaran proses pembelajaran membaca Al-Qur’an. Faktor pendukung berasal dari motivasi internal santri yang tinggi, sedangkan faktor penghambat termasuk rendahnya motivasi dan keterbatasan kemampuan dasar membaca Al-Qur’an di kalangan sebagian santri
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.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".