PENERAPAN MEDIA PEMBELAJARAN ONLINE DI MASA COVID 19 DI SMP NEGERI 1 SUNGGAL
Bibliographic record
Abstract
Peristiwa pandemik Covid-19 sangat berdampak bagi kehidupan manusia saat ini, khususnya di bidang pendidikan. Sekolah-sekolah diharuskan untuk menghentikan pembelajaran tatap muka menjadi pembelajaran dalam jaringan (pembelajaran online). Salah satunya adalah SMP Negeri 1 Sunggal. Sekolah tersebut juga terkena dampak buruk dari pandemik sehingga banyak para peserta didik kesulitan dalam menerima pembelajaran dari para pendidik. Selama ini, proses pembelajaran dilakukan hanya dengan menggunakan aplikasi WhatsApp (Wa) sehingga proses pembelajaran berlangsung secara tidak maksimal. Untuk itu, kami melakukan pengabdian masyarakat di sekolah ini guna memberikan sosialisasi pembelajaran menggunakan Google classroom dan Zoom kepada para pendidik agar dapat lebih meningkatkan hasil belajar peserta didik. Para pendidik sangat antusias dan ikut berpartisipasi dalam kegiatan pengabdian masyarakat ini dengan alasan bahwa media Google classroom dan Zoom sangat bagus diterapkan karena dapat menampilkan materi dan video pembelajaran dengan kapasitas besar sehingga pembelajaran berjalan lebih efektif dan efisen, baik secara teori maupun praktek.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.380 | 0.145 |
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".