BIAYA BBM AKIBAT KEMACETAN DI PERSIMPANGAN WILAYAH JABODETABEK FUEL COSTS BECAUSE OF CONGESTION IN THE INTERSECTION OF JABODETABEK
Bibliographic record
Abstract
Pertumbuhan kendaraan di wilayah Jabodetabek cukup tinggi mencapai 15-20% per tahun, tidak seimbang dengan pertumbuhan jalan yang hanya 0.01% per tahun, sehingga diperkirakan pada Tahun 2014 akan terjadi kemacetan total di DKI Jakarta dan sekitarnya. Kemacetan telah mengakibatkan kerugian waktu, energi, kesehatan fisik maupun psikis. Dalam penelitian ini dihitung biaya BBM akibat kemacetan di persimpangan di wilayah Jabodetabek. Berdasarkan analisis dengan menggunakan Contram dalam penelitian ini, dapat diketahui biaya BBM yang dikeluarkan akibat kemacetan Tahun 2011 di persimpangan rawan macet di wilayah Jabodetabek sebagai berikut: DKI Jakarta ±3,7 triliun rupiah; Bogor ±97,7 milyar rupiah; Depok ±259,3 milyar rupiah; Tangerang ±488,7 milyar rupiah, Bekasi ±360 milyar. Total biaya BBM tahun 2011 di persimpangan wilayah Jabodetabek ±4,9 triliun rupiah, dan diperkirakan tahun 2016 meningkat menjadi ±6,09 triliun rupiah.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".