<b>Pemanfaatan Lahan Bekas Tambang Menjadi Pariwisata </b><b>d</b><b>i Kawasan Benteng Kutopanji Kecamatan Belinyu</b><b> </b>
Bibliographic record
Abstract
Penelitian ini membahas pemanfaatan lahan bekas tambang di kawasan Benteng Kuto Panji, Kecamatan Belinyu, Kabupaten Bangka, sebagai upaya transformasi pascatambang menuju kawasan wisata berkelanjutan. Aktivitas pertambangan timah telah meninggalkan lahan terdegradasi, sehingga diperlukan rehabilitasi berbasis lingkungan dan sosial. Metode yang digunakan adalah observasi lapangan, survei masyarakat, dan analisis deskriptif kualitatif untuk mengidentifikasi potensi, bentuk pemanfaatan lahan, serta dampak sosial-ekonomi kawasan. Hasil penelitian menunjukkan bahwa pemanfaatan lahan bekas tambang menjadi wisata air, sejarah, dan edukasi memberikan manfaat ekologis melalui penghijauan dan konservasi air, serta manfaat ekonomi berupa peningkatan pendapatan dan penguatan UMKM lokal. Pengelolaan dilakukan secara kolaboratif antara pemerintah daerah, Yayasan Panji Mulia, dan masyarakat sesuai prinsip community-based tourism. Strategi pengembangan meliputi revitalisasi ekologis, pemberdayaan ekonomi lokal, serta promosi wisata terpadu sesuai arah RIPPARDA Kabupaten Bangka 2019-2025 dan RTRW 2024-2044. Kawasan ini diharapkan menjadi contoh pengelolaan pascatambang yang seimbang antara aspek lingkungan, sosial, dan ekonomi.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.082 | 0.018 |
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".