KAJIAN REFORMASI DAN PENGEMBANGAN ANGKUTAN DI TENGAH PANDEMI COVID-19 DI KABUPATEN SIDOARJO
Bibliographic record
Abstract
Sidoarjo merupakan bagian dari Gerbangkertosusila yang merupakan Metropolitan areas, maka diperlukan sarana dan prasarana yang mampu menunjang kebutuhan kota bersamaan dengan pandemi Covid-19 perlu dilakukan revitasliasai angkutan umum yang fundamental. Menurut survei yang dilakukan dengan metode AHP didapatkan model Y= 0,158X1 + 0,187X2 + 0,135X3 + 0,156X4 + 0,126X5 + 0,131X6 + 0,066X7 + 0,042X8 dari hasil perhitungan menunjukan bahwa kota Sidoarjo sudah siap untuk dikembangkan. Pengembangan yang dilakukan adalah mengembangkan angkutan eksisting rute Terminal Purabaya – Terminal Porong menjadi angkutan massal berbasis jalan yaitu Bus sedang dengan kapasitas 30 penumpang, yang memiliki waktu sirkulasi 1 jam 49,25 menit/trip, dengan load factor 77%, headway 11,55 menit, dan armada yang butuhkan 12 unit armada, serta tarif sementara yang ditentukan menurut BOK Rp. 8.334,-. Revitalisasi kepada angkutan eksisting adalah dengan melakukan scraping dengan cara mererouting angkutan eksisting dengan dijadikan feeder, peremajaan angkutan eksisting, dijual ke luar kota, dan apabila sudah sangat tidak laik jalan dijual rongsokan dibesi tua dengan metode kiloan.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".