Estimasi Volume Pengerukan Pelabuhan Tanjung Laut Dengan Metode Integrasi Numerik
Bibliographic record
Abstract
ABSTRAKPerhitungan volume pengerukan pada suatu pelabuhan diketahui dapat dilakukan dengan berbagai metode. Pada penelitian ini, algoritma perhitungan integrasi numerik klasik diaplikasikan untuk mengestimasi volume pengerukan Pelabuhan Tanjung Laut. Perhitungan dilakukan dengan menggunakan berbagai metode dasar pada integrasi numerik, yaitu dengan tiga pendekatan yang berbeda: aturan titik tengah (midpoint rule), aturan trapesium (trapezoidal rule), dan aturan simpson (Simpson’s rule). Data yang digunakan pada penelitian ini adalah data batimetri Pelabuhan Tanjung Laut hasil survey yang dilakukan oleh PT Marindo Utama Penata Kawasan pada tahun 2016. Hasil perhitungan dengan menggunakan pendekatan integrasi numerik dibandingkan dengan data volume pengerukan yang didapatkan dari PT Marindo Utama Penata Kawasan. Estimasi volume pengerukan dengan pendekatan integrasi numerik tersebut menghasilkan nilai galat dan kecepatan konvergensi yang bervariasi. Analisis perbandingan ketiga pendekatan yang berbeda dalam menghitung volume pengerukan dilakukan pada penelitian ini untuk mengetahui metode mana yang paling akurat.Kata kunci: Integrasi Numerik, Volume Pengerukan ABSTRACTThe volume of dredging at a port can be calculated using various methods. In this study, the classic numerical algorithm of integration was applied to estimate the dredging volume of Tanjung Laut Port. Calculations are performed using basic methods of numerical integration, differing in a way of approximation: the midpoint rule, the trapezoidal rule, and Simpson's rule. The data used in this research is the bathymetric survey data of Tanjung Laut Port from PT Marindo Utama Penata Kawasan in 2016. The calculation results using the approximation methods of numerical integration are compared with the dredging volume data obtained from PT Marindo Utama Penata Kawasan. The approximated value of the dredging volume obtained, but they are determined with various errors and speed of convergence to the correct result. A comparative analysis of three different approaches to estimating dredging volume was carried out in this study to find out which method is the most accurate. Keywords: Numerical Integration, Dredging Volume
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.013 | 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".