Bibliographic record
Abstract
Abstrak: Ketahanan pangan merupakan hak dasar yang dimiliki oleh setiap lapisan masyarakat. Terpenuhinya kebutuhan pangan di setiap negara dipengaruhi oleh kondisi fisik dan social. Kondisi fisik berupa sumber daya alam terutama di Indonesia bergantung pada sector pertanian dan perkebunan sebagai komoditi utama. Ketahanan pangan merupakan materi pada Mata Pelajaran Geografi kelas XI SMA. Penelitian dan pengembangan ini bertujuan untuk menghasilkan produk penunjang pembelajaran geografi dan menguji kualitas produk. Penelitian ini menggunakan metode Research and Development(R&D) dengan model Borg&Gall yang telah di modifikasi menjadi enam tahap pengembangan, yaitu 1)penelitian dan pengumpulan informasi, (2) Perencanaan, (3)pengembangan draf awal, (4) uji coba lapangan awal, (5) revisi produk, (6) produk akhir dan implementasi . Berdasarkan hasil dari validasi ahli materi menunjukkan presentase sebesr 92,8% dengan kriteria interpretasi sangat valid pada empat aspek (penyajian, kelayakan isimateri, bahasa dan belajar mandiri). Angket respon peserta didik menunjukkan presentase sebesar 87,3% hasil dipresentase ini menunjukkan bahwa peserta didik tertarik dan mampu memahami isi dari produk yang dikembangkan yakni suplemen buku. Berdasakan hasil yang telah dipaparkan menunjukkan Produk pengembagan suplemen bahan ajar layak untuk digunakan sebagai penunjang materi dalam pembelajaran geografi.
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.533 | 0.351 |
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".