Optimalisasi Pelayanan TPS3R di Kelurahan Panjunan Menggunakan Metode Contingent Valuation Method
Bibliographic record
Abstract
Recycling Facility Hikmah was built to provide solid waste management in the Panjunan Sub-district, Astanaanyar District, Bandung City. Recycling Facility Hikmah has the ability to operate continuously, but is still not running optimally due to cost constraints. This research was conducted to identify the potential for improving Recycling Facility management based on residents' willingness to participate in improving waste services through increasing retribution. The Contingent Valuation Method (CVM) is used as a survey technique using direct questionnaires and bidding game techniques, while statistical analysis will be carried out to determine the relationship between the observed variables. Based on the research results, the Willingness to Pay (WTP) value was obtained for 118 people from the 145 respondents interviewed. The Estimated WTP Value (EWTP) is IDR 6,822 and the Total WTP (TWTP) is IDR 4,848,866/month. Based on multiple linear regression analysis, the WTP value for Panjunan Village is influenced by the type of work and total income.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".