Kesesuaian Wisata di Pantai Pasir Panjang, Kelurahan Sedau, Kecamatan Singkawang Selatan, Kota Singkawang, Provinsi Kalimantan Barat
Bibliographic record
Abstract
Kota Singkawang adalah salah satu tujuan destinasi wisata yang ada di Kalimantan Barat. Kawasan pesisir Kota Singkawang dikembangkan sebagai objek wisata pantai. Pantai Pasir Panjang merupakan salah satu objek wisata pantai yang terkenal di Kota Singkawang. Pantai Pasir Panjang memiliki panorama berupa Laut Natuna dan pulau-pulau kecil yang ada di seberangnya. Aktivitas wisata di pantai harus mempertimbangkan faktor kenyamanan, keamanan, dan keselamatan pengunjung, sehingga perlu dilakukan evaluasi kesesuaian wisata pantai. Tujuan dari penelitian ini adalah untuk mengevaluasi tingkat kesesuaian wisata di Pantai Pasir Panjang. Metode yang digunakan terdiri dari metode survei lapangan, metode wawancara, serta metode skoring dan pembobotan. Skoring dan pembobotan dilakukan dengan sepuluh parameter berupa tipe pantai, lebar pantai, material dasar perairan, kecepatan arus, kecerahan perairan, kemiringan pantai, tutupan lahan pantai, biota berbahaya, dan ketersediaan air tawar. Hasil kesesuaian wisata rekreasi pantai pada Pantai Pasir Panjang bernilai sebesar 77,78% yang termasuk kategori sesuai (S2). Upaya pengelolaan perlu dilakukan guna meningkatkan kesesuaian wisata di Pantai Pasir Panjang.Kata Kunci: Evaluasi; Kesesuaian Wisata; Pantai; Pesisir; Wisata
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".