Persepsi Guru Sejarah Terhadap Implementasi Kurikulum 2013 pada Mata Pelajaran Sejarah: Survei Guru Sejarah di SMAN Se-Jakarta Barat
Bibliographic record
Abstract
This study aims to analyze the perceptions of history teachers on the implementation of the Kurikulum 2013 on the subject of history by surveying the history teachers in West Jakarta Senior High School. This study used survey research method with data collection techniques through questionnaires distribution to teachers of history subjects in West Jakarta Senior High School which amounted to 48 respondents. The result of this research is perception of history teacher in West Jakarta Senior High School about implementation of Kurikulum 2013 have very good perception about Kurikulum 2013 with percentage 88,27%. It can be said that the history teacher can receive, understand, and know the Curriculum change from Kurikulum 2006 (KTSP) to Kurikulum 2013 Penelitian ini bertujuan untuk menganalisis persepsi guru sejarah terhadap implementasi Kurikulum 2013 pada mata pelajaran sejarah dengan mensurvei guru sejarah yang ada di SMAN wilayah Jakarta Barat. Penelitian ini menggunakan metode penelitian survei dengan teknik pengumpulan data melalui penyebaran kuesioner kepada guru-guru mata pelajaran sejarah yang ada di SMAN wilayah Jakarta Barat yang berjumlah sebanyak 48 responden. Hasil dari penelitian ini adalah persepsi guru sejarah SMA Negeri di wilayah Jakarta Barat mengenai implementasi Kurikulum 2013 memiliki persepsi yang sangat baik tentang Kurikulum 2013 dengan presentase 88,27%. Hal ini dapat dikatakan bahwa guru sejarah dapat menerima, memahami, dan mengetahui adanya perubahan Kurikulum dari Kurikulum 2006 (KTSP) menjadi Kurikulum 2013.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".