Pendidikan Karakter Berbasis Sumber Daya Insani (SDI) di Pondok Pesantren
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui konsep pendidikan karakter berbasis sumber daya manusia di pondok pesantren. Metode dalam penelitian ini menekankan pada jenis studi kepustakaan yang diperoleh dari buku-buku yang berkaitan dengan definisi karakter, pembentukan karakter, pendidikan pondok pesantren & proses pembentukan karakter santri berbasis Sumber Daya Manusia di pondok pesantren. Teknik pengumpulan data melalui buku, jurnal, artikel dan majalah serta internet yang berkaitan dengan pendidikan karakter, pendidikan pondok pesantren & Sumber Daya Manusia. Analisis data menggunakan teknik analisis yang dikemukakan oleh Miles dan Huberman dengan tahapan reduksi data, penyajian data dan penarikan kesimpulan (verifikasi). Hasil kajian menunjukkan bahwa pesantren menyelenggarakan pendidikan dengan tujuan menanamkan karakter santri berbasis Sumber Daya Manusia (SDI) yang mengarah pada iman dan taqwa kepada Allah SWT, berakhlak mulia, dan tradisi pesantren untuk mengembangkan kemampuan, pengetahuan, dan keterampilan santi untuk menjadi ahli ilmu agama Islam (mutafaqqih fiddin) dan menjadi seorang muslim yang memiliki kecakapan keahlian untuk membangun kehidupan Islami di masyarakat.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".