Strategi Pengembangan Bank Sampah Sahdu Skala Kelurahan di Desa Tanimulya Kabupaten Bandung Barat
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
Out of four waste banks in the Tanimulya Village, Sahdu Waste Bank is the only proper waste bank in operation. Based on the 2019 West Bandung District’s Environmental Agency (Dinas Lingkungan Hidup Kebersihan) Strategic Plan, which stated the target in 2022, that it needs to reduce 10%, from the current 8% reduction of the waste generation through the solid waste management and waste bank facilites, prior to the landfill. One of the efforts that can be done is through the development of the Sahdu Waste Bank from the hamlet scale to the urban village scale by using the Waste Bank Indexing Method. Assessing the existing condition with the waste bank index, identification and compiling the recommendation towards parameters that need improvement. Based on the results of the assessment, a score of 53.2 (out of 100, and is considered as fairly good category), reveals 14 sub indicator that can be improved, which consist of 6 Sub Indicator of Management System, 6 Sub Indicator of Operational System, and 2 Sub Indicator of Waste Bank Facility. The value of the Sahdu Waste Bank can be increased to 88.3 (out of 100, and is considered as very good), which generates the reduction of 266.67% of waste, equal to 4 ton/month from 150 kg/month. That would make Sahdu Waste Bank contributes 1.6% from the reduction target of 10% for the West Bandung District waste.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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