PENGUATAN PENDIDIKAN KARAKTER MELALUI BUDAYA SEKOLAH DI SD NEGERI 1 SIGLI
Bibliographic record
Abstract
Abstrak: Penelitian ini bertujuan adalah: 1) menerapkan pendidikan karakter dalam budaya sekolah di SDN 1 Sigli, 2) mengetahui Apa saja nilai-nilai karakter dalam budaya sekolah yang diterapkan di SDN 1 Sigli, 3) mengetahui apa saja faktor penghambat dan faktor pendukung pendidikan karakter dalam budaya sekolah di SDN 1 Sigli. Penelitian ini adalah penelitian deskriptif dengan menggunakan pendekatan kualitatif. Subjek penelitian ini terdiri dari satu kepala sekolah, enam guru, dua guru ekstrakurikuler, tiga siswa kelas IV, V dan VI, dan komite sekolah. Seleksi penelitian subyek telah dengan pertimbangan tertentu. Percobaan dilakukan di SD Negeri 1 Sigli. Teknik pengumpulan data menggunakan wawancara, dokumentasi dan pengamatan moderat karena para peneliti hanya melakukan beberapa kegiatan yang dilakukan oleh pembicara. Teknik analisis data yang digunakan selama penelitian ini menggunakan model interaktif Miles dan Huberman, yaitu pengumpulan data, reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa pelaksanaan pendidikan karakter melalui budaya sekolah yang dilakukan di SD Negeri 1 Sigli meliputi intrakurikuler termasuk tadarus one day one ayat, senam massal, upacara bendera, peringatan hari besar, pergi perpustakaan. Selain kegiatan intrakurikuler, pelaksanaan pendidikan karakter melalui budaya sekolah di SD Negeri 1 Sigli juga dimanifestasikan dalam kegiatan ekstrakurikuler, yaitu pramuka, TPA, TIK,marching band, drama, dalail khairat, dan shalawatan. Kata Kunci: Karakter Siswa, Kultur Sekolah
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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 | 0.002 | 0.007 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.007 |
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".