KEBIJAKAN PEMERITAH DAN PENGELOLAAN DESTINASI KAWASAN PUNCAK DALAM MENJAWAB TANTANGAN OVERTOURISM DAN TRANSFORMASI DIGITAL
Bibliographic record
Abstract
Abstrak Pariwisata Kawasan Puncak Bogor menjadi wajah paradoks industri pariwisata: di satu sisi menjadi pendorong ekonomi, di sisi lain melahirkan persoalan overtourism seperti kemacetan, polusi, dan tekanan lingkungan. Penelitian ini mengkaji arah kebijakan pemerintah serta praktik pengelolaan destinasi yang dilakukan oleh pengelola lokal dalam menjawab tantangan tersebut. Pendekatan kualitatif berbasis kajian literatur digunakan dengan merujuk pada studi akademik, laporan kebijakan, dan publikasi organisasi internasional periode 2020-2025. Hasil penelitian menunjukkan bahwa kebijakan pemerintah daerah berfokus pada digitalisasi sistem kunjungan, penguatan tata kelola berbasis kolaborasi, serta regulasi zonasi. Sementara itu, pengelola destinasi mulai mengadopsi inovasi digital dan model Destination Management Organization (DMO). Namun, kesenjangan akses digital bagi UMKM lokal menjadi tantangan serius yang harus diatasi. Penelitian ini menyimpulkan bahwa masa depan pariwisata di Kawasan Puncak hanya akan berkelanjutan apabila kebijakan publik dan praktik pengelolaan bersifat inklusif, berbasis data, serta menempatkan keseimbangan ekonomi, sosial, dan lingkungan sebagai tujuan utama. Kata kunci : Kebijakan Pemerintah, Pengelolaan Destinasi, Overtourism, Transformasi Digital. Abstract Tourism in the Puncak highlands of Bogor illustrates the paradox of the tourism industry: on the one hand, it drives economic growth, yet on the other, it generates overtourism issues such as congestion, pollution, and environmental pressure. This study examines the direction of government policies and the management practices implemented by local destination managers in addressing these challenges. A qualitative approach based on literature review was employed, drawing from academic studies, policy reports, and international organizational publications from 2020-2025. The findings reveal that local government policies have focused on digitalizing visitor registration systems, strengthening collaborative governance, and implementing zoning regulations. Meanwhile, destination managers have begun adopting digital innovations and the Destination Management Organization (DMO) model. However, digital access gaps for local SMEs remain a critical challenge that must be addressed. The study concludes that the future of tourism in Puncak will only be sustainable if public policies and management practices are inclusive, data-driven, and committed to balancing economic growth, social equity, and environmental sustainability. Keywords : Government Policy, Destination Management, Overtourism, Digital Transformation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.009 |
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".