SOSIALISASI KESIAP SIAGAAN TERHADAP ERUPSI GUNUNG BROMO KEPADA PELAKU WISATA DAN MASYARAKAT
Bibliographic record
Abstract
Indonesia, sebagai negara kepulauan terbesar di dunia yang terletak di sepanjang Cincin Api Pasifik, sangat rentan terhadap berbagai bencana geologi seperti gempa bumi, tsunami, dan letusan gunung berapi. Salah satu gunung berapi aktif yang terkenal di Indonesia adalah Gunung Bromo, yang menjadi tujuan wisata populer namun juga menyimpan potensi bahaya erupsi. Penelitian ini bertujuan untuk menilai efektivitas program sosialisasi yang dilakukan oleh Pusat Vulkanologi dan Mitigasi Bencana Geologi (PVMBG) dalam meningkatkan kesadaran masyarakat dan pelaku wisata di sekitar Gunung Bromo tentang mitigasi bencana. Metode penelitian yang digunakan adalah penelitian tindakan sosial dengan melibatkan total 70 responden yang terdiri dari pemangku kepentingan dan masyarakat lokal. Program sosialisasi mencakup seminar, lokakarya, dan simulasi kesiapsiagaan bencana. Hasil penelitian menunjukkan adanya peningkatan pemahaman tentang mitigasi bencana, dengan peningkatan rata-rata sebesar 7.5% di kalangan pemerintah dan 19.45% di kalangan non-pemerintah. Penelitian ini menyimpulkan bahwa sosialisasi yang rutin dan berkelanjutan penting dilakukan untuk meningkatkan kesiapsiagaan bencana dan meminimalisir risiko bencana di masa depan.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".