Pengelolaan Sampah Rumah Tangga Berbasis Masyarakat Di Kelurahan Nginden Jangkungan, Kecamatan Sukolilo
Bibliographic record
Abstract
Pengelolaan sampah merupakan salah satu masalah yang ada di Surabaya. Sebagai salah satu kota terbesar di Indonesia, Surabaya memiliki kepadatan penduduk yang tinggi. Dengan tingkat kepadatan penduduk yang tinggi itu Surabaya menghasilkan banyak sampah organik maupun non-organik. Maka dari itu, diperlukan pengelolaan sampah yang optimal agar tidak terjadi pencemaran lingkungan. Bank sampah adalah salah satu bentuk pendekatan yang berbasis masyarakat. Pemberdayaan masyarakat difokuskan pada pengelolaan sampah di Kelurahan Nginden Jangkungan, khususnya di RT. 04 RW. 01. Mekanisme pengelolaan sampah melalui bank sampah didasarkan atas Peraturan Menteri Lingkungan Hidup Pasal 5 No. 13 Tahun 2012 yaitu tentang Pedoman Pelaksanaan 3R. Tahapan yang pertama ialah memilah sampah sesuai dengan jenisnya, lalu dibawa ke bank sampah. Selanjutnya, warga melakukan pendaftaran dan menimbang sampah yang telah dibawanya. Total sampah yang sudah ditimbang kemudian dicatat dalam buku tabungan masyarakat.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.017 |
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".