Arahan Peningkatan Keberlanjutan Hutan Kota di Kota Surabaya
Bibliographic record
Abstract
Hutan Kota Surabaya merupakan salah satu ruang terbuka hijau yang belum sepenuhnya terkoordinir dengan baik dari segi sumber daya vegetasi, komunitas, dan pengelolaannya. Selain itu, luasan dan fungsi hutan kota di surabaya saat ini masih belum sesuai dengan kebutuhan dan Perda No. 15 tahun 2014 tentang Hutan kota. Tahapan penelitian ini diawali hasil content analysis adalah variabel yang berpengaruh yang terbagi dalam 3 faktor yakni sumberdaya vegetasi, komunitas dan pengelolaan. Selanjutnya, dilakukan penilaian tingkat keberlanjutan dengan menggunakan teknik skoring. Kemudian perumusan arahan peningkatan keberlanjutan hutan kota menggunakan analisis deskriptif komparatif. Hasil dari penelitian ini menunjukkan bahwa berdasarkan hutan kota berkelanjutan tinggi (hutan kota Pakal, hutan kota Balasklumprik, hutan kota Sumurwelut, dan Kebun Binatang Surabaya) berfokus pada strategi koordinasi antar dinas, kerjasama industri hijau dan warga serta peraturan yang tegas. Sedangkan berkelanjutan sedang dan rendah (hutan kota Lempung, hutan kota Sambikerep, hutan kota Gununganyar, hutan kota Jeruk, hutan kota Penjaringan Sari dan hutan kota Prapen) berfokus pada penanaman secara intensif, pendanaan secara kreatif, pembangunan fasilitas dan perekrutan tenaga kerja sesuai dengan luasan hutan kota
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".