Sustainable Marine Tourism Planning in South Malang: A Feasibility and Zoning Approach for Balanced Development
Bibliographic record
Abstract
Sustainable marine tourism development requires a strategic balance between environmental conservation and economic growth.This study assesses the feasibility of marine tourism in South Malang by evaluating 50 coastal sites using a multi-criteria decision analysis (MCDA) framework.The assessment incorporates environmental suitability, infrastructure readiness, market potential, community engagement, and regulatory support to determine the most viable locations for tourism development.Data collection involved field observations, stakeholder interviews, and spatial analysis using Geographic Information Systems (GIS).The results identify key tourism zones, with high-feasibility sites such as Watu Lepek and Pasir Panjang demonstrating strong environmental quality and tourism potential.Conversely, lower-scoring sites like Sipelot and Gatra require conservation prioritization due to ecological sensitivity.Considering South Malang's current early-stage tourism conditions, particularly following improved coastal access via the newly opened South Cross Road, the study proposes a zoning strategy aligned with Butler's Tourism Area Life Cycle (TALC), specifically the exploration phase and applies the Limits of Acceptable Change (LAC) framework to proactively manage ecological thresholds.The study proposes a zoning strategy that integrates tourism growth with environmental management, ensuring that development aligns with sustainability principles.Additionally, it highlights the importance of infrastructure investment, stakeholder participation, and adaptive conservation policies in maintaining ecological resilience while fostering regional economic benefits.This research contributes to sustainable tourism planning by offering a structured approach to site evaluation and zoning, supporting policymakers in making data-driven decisions that balance tourism expansion with long-term ecological protection.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".