BANGKITAN DAN TARIKAN PERGERAKAN DI KAWASAN PENDIDIKAN KOTA BANDAR LAMPUNG
Bibliographic record
Abstract
Abstract The movement of people to fulfill their needs must be well planned, so that traffic congestion can be avoided. The increasing population in Bandar Lampung has an impact on the number of movements as a whole, and one of them is in the school area on Jalan Cendana-Jalan Ir. H. Juanda. This study aims to determine the generation and attraction models of movement in the school area, on Jalan Cendana-Jalan Ir. H. Juanda, Bandar Lampung. This study shows that the factors that influence the trip generation and trip attraction in the study area are the number of classrooms, the number of teachers and staffs, and student daily allowances. In addition, the trip generation and trip attraction that occur are large enough to affect traffic, especially in the morning, which indicates high land use activities in the morning in the area. Keywords: school area; traffic congestion; trip generation; trip attraction. Abstrak Pergerakan manusia untuk memenuhi kebutuhannya harus direncanakan dengan baik, agar kemacetan lalu lintas dapat dihindari. Jumlah penduduk di Kota Bandar Lampung yang terus meningkat berdampak pada jumlah pergerakan secara keseluruhan, dan salah satunya pada kawasan pendidikan di Jalan Cendana-Jalan Ir. H. Juanda. Penelitian ini bertujuan untuk mengetahui model bangkitan dan tarikan pergerakan di kawasan pendidikan, di Jalan Cendana-Jalan Ir. H. Juanda, Bandar Lampung. Studi ini menunjukkan bahwa faktor-faktor yang memengaruhi bangkitan dan tarikan pergerakan di wilayah studi adalah jumlah ruang kelas, jumlah guru dan tenaga kependidikan, serta uang saku murid per hari. Selain itu, bangkitan dan tarikan pergerakan yang terjadi cukup besar untuk memengaruhi lalu lintas, terutama di pagi hari, yang menandakan tingginya aktivitas guna lahan pada pagi hari di kawasan tersebut. Kata-kata kunci: kawasan pendidikan; kemacetan lalu lintas; bangkitan pergerakan; tarikan pergerakan.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".