ANALISIS KAPASITAS TERMINAL PENUMPANG BANDAR UDARA SENTANI DI JAYAPURA
Bibliographic record
Abstract
Papua merupakan salah satu daerah yang menjadikan transportasi udara sebagai pilihan utama untuk memenuhi kebutuhan mobilisasi. Seiring meningkatnya kegiatan pariwisata di Jayapura, maka meningkat pula jumlah pengunjung yang datang. Dengan adanya peningkatan jumlah penumpang di Bandar Udara Sentani, terminal penumpang terkadang mengalami penumpukan di beberapa area. Perlu di lakukan evaluasi terhadap kapasitas terminal penumpang yang ada saat ini dan analisa kebutuhan luas terminal penumpang dalam menampung sirkulasi pergerakan penumpang pada waktu sibuk, dengan memperhitungkan peningkatan penumpang dimasa mendatang, sehingga didapat kesesuaian antara kapasitas terminal penumpang dengan luas terminal penumpang saat ini. Hasil penelitian untuk terminal penumpang keberangkatan, luas aktual terminal mampu menampung sirkulasi pergerakan penumpang pada waktu sibuk yaitu sebesar 220 penumpang, sementara terminal kedatangan kurang mampu untuk menampung sirkulasi pergerakan penumpang kedatangan pada waktu sibuknya yaitu sebesar 232 penumpang. Untuk LOS sendiri berdasarkan standar IATA mendapatkan hasil yang memenuhi standar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".