Pengaruh Metode Menulis Berantai terhadap Kemampuan Menulis Cerita Pendek Siswa Kelas IX Sekolah Menengah Atas
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui seberapa besar pengaruh metode menulis berantai terhadap kemampuan menulis cerita pendek siswa kelas XI SMA Negeri 1 Cot Girek. Jenis pendekatan yang digunakan yaitu pendekatan kuantitatif, jenis penelitian yaitu penelitian eksperimen dengan rancangan quasi eksperimental designs (eksperimen semu). Desain penelitian yang digunakan adalah pretest-posttest control group design. Teknik pengumpulan berupa tes menulis cerita pendek dan lembar penilaian. Penelitian dilakukan pada kelas XI dengan jumlah populasi sebanyak 164 siswa dan sampel yang diambil menggunakan teknik simple random sampling yaitu dua kelas sebagai kelas eksperimen dan kelas kontrol. Hasil penelitian ini yaitu nilai rata-rata posttest kelas eksperimen sebanyak 75,59 yang sudah memenuhi KKM dan nilai rata-rata posttest kelas kontrol sebanyak 70,2 yang belum memenuhi KKM. Hasil uji t juga membuktikan bahwa penelitian yang dilakukan oleh peneliti dikatakan berhasil karena nilai signifikansi < nilai alpha (0,047 < 0,05), dan t hitung > t tabel (2.031 > 1.675) maka Ha diterima dan Ho ditolak. Peneliti menyimpulkan bahwa metode menulis berantai efektif terhadap kemampuan menulis cerita pendek siswa kelas XI SMA Negeri 1 Cot Girek.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 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".