PENGGUNAAN MODEL MEANINGFUL INTRUCTION DESIGN DALAM MENINGKATKAN PEMBELAJARAN FIQIH BAGI SISWA DI MADRASAH TSANAWIYAH
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRAK
 Penelitian ini bertujuan untuk mengimplementasi Model Pembelajaran Meaningful Intruction Design (MID) adapun penelitian ini dilaksanakan dalam 2 siklus. Penelitian ini merupakan penelitian tindakan kelas. Penelitian ini terdiri dari 4 alur yaitu: (1) Perencanaan, (2) Tindakan, (3)Pengamatan, (4) Refleksi. Subjek dalam penelitian ini adalah Guru Fiqih dan siswa kelas VII.2 yang terdiri dari 34 Orang. Instrumen penelitian ini, yaitu observasi, tes, wawancara, dan dokumentasi. Hasil penelitian menunjukan adanya peningkatan persentase ketuntasan hasil belajar Fiqih pada setiap siklus, pada siklus 1 persentase ketuntasan belajar siswa mencapai 50%, dengan jumlah siswa 17 orang yang mencapai KKM dengan nilai rata-rata 60, dan setelah dilaksanakan siklus 2 persentase meningkat menjadi 91% dengan jumlah siswa 31 orang yang mencapai KKM dengan rata-rata nilai 77. Hal ini membuktikan bahwa model pembelajaran Meaningful Intruction Design (MID) bisa meningkatkan hasil belajar Fiqih kelas VII.2 Madrasah Tsanawiyah Swasta Penyengat Olak Provinsi Jambi.
 
 Kata Kunci: Model Meaningful Intruction Design, Hasil Belajar, Fiqih
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it