New Orientation Strategy into Domestic Market for Bali Tourism Destination after the COVID-19 Pandemic
Bibliographic record
Abstract
This research aims to determine the New Orientation Strategy into Domestic Market for Bali Tourism Destination after the COVID-19 Pandemic.This research conducted a study of secondary data and facts regarding the situation of Bali tourism destinations.The data is presented through a descriptive qualitative analysis based on the 4A factors (Attraction, Accessibility, Amenities, Ancillary), and also explains the motivation of domestic tourists traveling to Bali.The strategy offered is that promotion outside these areas needs to be increased.The strategy offered is to maintain or improve the quality of service, security, and arrangement of holiday or recreation places.Promotion through electronic media needs to be increased, and tourist satisfaction must be maintained and continued in both quality and quantity.The development of tourism from a cultural and environmental perspective is still very relevant as a reference for tourism development in Bali.The future development of Bali tourism should be more directed at efforts to conserve and organize the coastal/sea, mountains, lakes, and rice fields.The development of cultural tourism attractions is more oriented towards the revitalization of these types of cultural tourism attractions.The strategy offered is improving service quality, and security and structuring shopping centers that provide local products.The strategy offered is to increase the competitiveness of tourist attractions in other areas of Bali.The strategy offered is improving the quality of restaurant businesses, diversifying souvenirs, and empowering craftsmen groups.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".