Pengaruh Harga Bensin terhadap Kecelakaan Lalu Lintas di Indonesia
Bibliographic record
Abstract
Kecelakaan lalu lintas menempati urutan kesembilan penyebab kematian di Indonesia. Kebanyakan penelitian kecelakaan di Indoneia menitikberatkan pada faktor manusia, kendaraan, dan lingkungan, tetapi belum ada yang memasukkan faktor-faktor ekonomi ke dalam modelnya. Tujuan penelitian ini adalah ingin mengetahui pengaruh harga riil bensin terhadap kecelakaan lalu lintas di Indonesia serta faktor-faktor yang memengaruhinya. Penelitian ini menggunakan data time series Indonesia dari tahun 1970 hingga 2013 dan menggunakan OLS dengan variabel instrumen harga minyak mentah dunia. Hasil estimasi menunjukkan bahwa harga riil bensin dan kebijakan penggunaan lampu utama sepeda motor tidak signifikan terhadap kecelakaan lalu lintas. Sedangkan PDB riil dan jalan aspal signifikan berpengaruh menurunkan kecelakaan. Namun, sepeda motor berdampak signifikan meningkatkan kecelakaan lalu lintas.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".