Analisa Tingkat Pemanfaatan Lapangan Penumpukan Peti Kemas Pelabuhan Yos Sudarso Ambon
Bibliographic record
Abstract
Pelabuhan Ambon adalah pelabuhan yang berlokasi di kota Ambon Propinsi Maluku , terletak di wilayah bagian timur sehingga memiliki ciri transportasi laut yang sangat dominan akibat bentang alam serta geografisnya yang sulit untuk pengembangan transportasi darat. Tujuan Penelitian ini adalah untuk Menganalisis kinerja lapangan penumpukan Pelabuhan Yos Sudarso Ambon untuk kondisi eksisting (2019), Menentukan model kebutuhan kapasitas lapangan penumpukan dan Menganalisis kapasitas optimal Lapangan Penumpukan Petikemas Pelabuhan Yos Sudarso Ambon untuk kondisi eksisting (2019) sampai 20 tahun mendatang. Perhitungan proyeksi trafik petikemas diproyeksikan dengan menggunakan metode regresi sederhana yaitu regresi linier dan eksponensial. Tingkat Pemanfaatan dan pemakaian lapangan penumpukan peti kemas tahun 2019 nilai YOR di Pelabuhan Yos Sudarso Ambon masih memadahi, namun pada analisis nilai YOR untuk 10 tahun mendatang, yakni pada jangka menegah tahun 2032 nilai YOR di pelabuhan Yos sudarso Ambon mencapai angka 77.54 % dan di jangka panjang tahun 2038 nilai YOR di pelabuhan Yos sudarso Ambon mencapai angka 145.76 % dimana kapasitasnya sudah tidak mencukupi (Overload)
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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".