Perceptions of Marine Tourism in Lampung Bay's Small Islands: A Comparative Study
Bibliographic record
Abstract
Pasaran and Permata Islands, situated within the Lampung Bay cluster, offer unique tourist experiences yet have not succeeded in attracting substantial visitor interest.This study aims to analyze perceptions of marine tourism on these small islands located in Bandar Lampung City, Lampung Province, Indonesia.A total of 228 respondents, visiting Pasaran and Permata Islands, participated in the study.The adopted analytical method was Exploratory Factor Analysis, supplemented by f-tests and t-tests.The analysis of 23 tourism perception attributes yielded five distinct factors: tourist access, supporting facilities, natural resources, cleanliness, and additional supporting factors.Notably, the perceptions of the two islands differed significantly, attributable to variations in attractions, facilities, accommodation, and access.This divergence manifested in tourists' perceptions analyzed by gender, age, and income.The insights suggest that both islands require enhancements in specific areas.Pasaran Island necessitates advancements in 'supporting factors', while 'tourist access' is an area for improvement on Permata Island.The findings contribute to the understanding of marine tourism perceptions and provide actionable suggestions for enhancing the tourist experience on these islands.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".