Analysis of Fares and Subsidy Needs for Public Transportation using The Vehicle Operating Cost Approach (Case Study: Corridor 2 Trans Cirebon)
Bibliographic record
Abstract
Public transportation subsidies or what is called the Public Service Obligation (PSO) is an important indicator in the public transport system to ensure the sustainability of the operation of the public transportation system. Subsidies are government interventions in controlling transportation fares so that people can use public transportation at affordable fares. This study aims to provide an overview of the determination of fares and the amount of subsidy needed in corridor 2 of Trans Cirebon. Fare analysis is determined using the vehicle operating cost and Willingness To Pay (WTP) approaches which will then form the basis for providing an overview of the subsidy that should be provided by the Government in an ideal Trans Cirebon operation. This research shows that: 1) the fare currently applied are still in accordance with the WTP value the people of Cirebon City; 2) for an ideal Trans Cirebon operation, a vehicle operating cost of Rp. 6,135,159,933.29/year is required; 3) the amount of subsidy required ranges from Rp. 5,705,919,933.29/year to Rp. 6,108,879,933.29/year depending on the achievement value of the load factor and the fare applied.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".