The Impact of Tourism on the Economy and Community Welfare in Labuan Bajo Area, Indonesia
Bibliographic record
Abstract
This study aims to analyze the impact of tourism on the economy and people's welfare in the Labuan Bajo area. This research was quantitative research with primary and secondary data. The data analysis method used was multiple linear regression analysis with the first structural equation related to the community's welfare (business actors) and the second related to macroeconomic indicators. The research was conducted through a survey of 221 respondents and collecting quarterly data on financial reports. The results showed that the average level of income of business actors who opened a business in tourist locations was higher than those who opened businesses outside tourist sites. The variables of the average length of stay, inflation, and investment significantly affected Regional Original Income in West Manggarai. A business's characteristics were the main determinants of people's welfare and not the perpetrators' characteristics. These results contributed to developing an integrated tourism model that is relevant to the tourist area of Labuan Bajo. The conclusion was that tourism impacted the West Manggarai Regency's economy, including increased local revenue, employment, and gross domestic income.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".