Evaluasi Kinerja Operasional Angkot Banjaran - Taman Cibaduyut Indah di Kabupaten Bandung
Bibliographic record
Abstract
Abstract. The Banjaran–Taman Cibaduyut Indah corridor shows significant movement potential, driven by predominant land uses such as residential areas (43.43%) and industrial/commercial zones (10.82%). The estimated trip generation reaches 124,186 movements, while the potential passenger demand accounts for only 16.17% (20,089 passengers). Users perceive the quality of public minibus (angkot) services—particularly in terms of travel time and cost efficiency, safety, security, and comfort—as inadequate. Therefore, operational performance must be evaluated using the standards set by the Decree of the Director General of Land Transportation No. SK.687/AJ.206/DRJD/2002 on Technical Guidelines for Urban Public Transport Operations. This study applies a mixed-method approach, combining quantitative and qualitative analysis, with data collected through primary and secondary sources. The findings indicate that six out of eight operational performance parameters require improvement, including load factor, time headway, travel time, service hours, vehicle frequency, number of operating vehicles, and passenger waiting time. Abstrak. Koridor Rute Banjaran – Taman Cibaduyut Indah merupakan wilayah yang memiliki potensi pergerakan besar, dilihat dari penggunaan lahan yang dominan yaitu permukiman (43,43%), dan industri & perdagangan jasa (10,82%). Potensi bangkitan pergerakan koridor ini sebesar 124.186 pergerakan, sedangkan permintaan potensial penumpang hanya 16,17% (20.089 penumpang). Penumpang menilai bahwa kualitas pelayanan angkot dari sisi efektivitas waktu dan biaya, keamanan, keselamatan, dan kenyamanannya masih kurang. Maka, perlu dievaluasi kinerja operasional angkotnya dengan standar pada kebijakan Keputusan Direktur Jenderal Perhubungan Darat Nomor SK.687/AJ.206/DRJD/2002 tentang Pedoman Teknis Penyelenggaraan Angkutan Penumpang Umum di Wilayah Perkotaan dalam Trayek Tetap dan Teratur. Metode pendekatan yang digunakan adalah kuantitatif dam kualitatif dengan metode analisis deskripsi kuantitatif, dan pengumpulan data primer dan sekunder. Hasil identifikasi menunjukkan bahwa terdapat 6 (enam) dari 8 (delapan) parameter kinerja operasional yang perlu diperbaiki, yaitu load factor, time headway, waktu perjalanan, waktu pelayanan, frekuensi kendaraan, kendaraan yang beroperasi, dan waktu tunggu.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".