Strategi Pengembangan Industri Pariwisata Pulau Kaniungan Kampung Teluk Sumbang Kecamatan Biduk Biduk
Bibliographic record
Abstract
Pemerintah Daerah Kabupaten Berau dalam hal Dinas Kebudayaan dan Pariwisata saat ini belum memiliki suatu strategi perencanaan dan pengembagan industri pariwisata yang komprehensif dan perencanaan dan pengembangan yang dilakukan masih bersifat sektoral. Data yang diperoleh menunjukkan bahwa terdapat penurunan jumlah angka wisatawan dimana pada tahun 2022 jumlah wisatawan yang berkunjung ke Pulau Kaniungan adalah sebanyak 3.171 jiwa sedangkan pada tahun 2023 hanya sebanyak 2.164 jiwa. Pengembangan dan pengelolaan industri pariwisata yang baik dibutuhkan untuk menangani permasalahan yang ada di Pulau Kaniungan. Tujuan dari penelitian ini adalah untuk mengetahui bagaimana kondisi eksisting industri pariwisata, serta strategi yang diperoleh berdasarkan analisis SWOT faktor internal dan eksternal, kemudian merumuskan strategi pengembangan industri pariwisata menggunakan analisis Quantitative Strategic Planning Matrix (QSPM). Hasil temuan yang didapatkan adalah terdapat 11 strategi pengembangan industri pariwisata yang dapat memberikan solusi komprehensif terhadap permasalahan industri pariwisata di Pulau Kaniungan. Kata-kunci : Pariwisata, Industri, Pengembangan, SWOT, QSPM
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".