Optimization of Marine Activities Based on Spatial Regional Planning and Geographical Approaches: A Case Study of Tol Laut Program in Indonesia
Bibliographic record
Abstract
Tol Laut is a marine activity that manages the maritime highway system in Indonesia to ensure and improve connectivity within the national logistics and supply chain system. This system arises because of the inequality of economic growth and development between several regions and provinces. The purpose of this program is to reduce high price disparities so that equity across regions can be achieved. However, this system has not run optimally. The performance of the program, which has entered its eighth year, is still less than 30%. Many problems arise that persist in causing the high price of goods. Hence, this study will identify the causes of the suboptimal Tol Laut by using spatial and geographic approaches on a sample of T-3 shipping route. Based on the spatial approach, it is found that the route is not optimal, so a strategy is obtained to create a new optimal route by producing a more efficient distance of 51,148 nm and a more effective time of 2 hours 18 minutes. Based on the geographical approach, the economic, social, and cultural factors that influence it were obtained. The identification of economic factors shows that high insurance premiums cause price disparities. Through this research, a strategy to produce more efficient and effective tariffs is obtained so as to reduce high disparities. This is important because Tol Laut is national strategic project that needs to be maintained.Received: 2024-04-30 Revised: 2025-08-15 Accepted: 2025-12-03 Published: 2025-12-04
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".