Keterampilan Membaca Bahasa Indonesia Bagi Penutur Asing Menggunakan Pendekatan Berbasis Teks Siswa Kelas 11 SMAK Santo Antonio Oecusse Timor Leste
Bibliographic record
Abstract
Keterampilan membaca pemahaman merupakan kunci utama dalam mengumpulkan pengetahuan. Namun, masih banyak guru yang mengajarinya dengan menggunakan metode penerjemahan kata demi kata, yang berdampak pada kurangnya pemahaman siswa terhadap teks. Penelitian ini bertujuan untuk mengeksplorasi penerapan pendekatan bahasa Indonesia bagi penutur asing di SMAK Santo Antonio Oecusse, Timor Timur. Metode penelitian yang digunakan adalah deskriptif kualitatif, dengan data diperoleh dari siswa kelas 11 IPS SMAK Santo Antonio Oecusse. Guru akan mengajarkan teknik pengumpulan data di kelas, dan analisis data dilakukan dengan mendeskripsikan observasi aktivitas siswa selama proses belajar mengajar. Penelitian ini diharapkan dapat memberikan wawasan baru dalam pengembangan metode pembelajaran yang efektif untuk meningkatkan pemahaman membaca siswa.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".