Peran Kebijakan dalam Peningkatan Performa Layanan BRT Transjakarta
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
Public transportation service improvement in urban area, such as Bus Rapid Transit (BRT), becomes the main issue among transport planners nowadays. BRT has been a popular transit system which provide an easy dan fast service for satisfying the transport needs, particularly in developing countries. This transport mode offers high quality mass transit system yet still in affordable cost, which is necessary for developing countries. Jakarta becomes the first Southeast Asia country who applied the BRT system. This study aims to gain insights towards the role of policies in facilitating the improvement of TransJakarta performance and reach 1 million passengers in early 2020. Understanding the policy aspect, both central and regional policies which can improve the public transport performance, will possibly provide a broader perspective among policymakers who developing and implementing the BRT systems, particularly in developing countries. For this purpose, conceptual framework was employed to explain how policy implementation could improve the BRT performance, which collected through secondary data, mostly various planning documents and TransJakarta operational reports. By using the qualitative approach, results show that various policies could facilitate the improvement of TransJakarta performances. The improvements occurred in line with the institutional reforms and the development of BRT system, such as routes, capacities, and integration with other mass transit systems.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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