Kearifan Lokal dalam Mitigasi Bencana di Wilayah Lereng Gunung Merapi Studi Kasus Kecamatan Cangkringan, Kabupaten Sleman
Bibliographic record
Abstract
Indonesia adalah negara yang rawan bencana geologis gempa bumi, tanah longsor, erupsi gunung api, dan tsunami. Sebagai konsekuensi kewajiban negara untuk melindungi rakyatnya maka pemerintah diharapkan mengambil langkah-langkah yang tepat untuk mengurangi risiko dan mempunyai rencana keadaan darurat untuk meminimalkan dampak bencana. Kesiapsiagaan dilakukan untuk memastikan upaya yang cepat dan tepat dalam menghadapi kejadian bencana. Tujuan dalam penelitian ini adalah merumuskan model konseptual living in harmony with disaster (mitigasi berbasis kearifan lokal) masyarakat lereng Gunungapi Merapi Kabupaten Sleman Provinsi Daerah Istimewa Yogyakarta. Sasarannya adalah mengidentifikasi kondisi eksisting masyarakat dalam aspek tanggap bencana dan mengidentifikasi pola proses mitigasi berbasis kearifan lokal masyarakat lereng Gungungapi Merapi Kabupaten Sleman yang disebut living in harmony with disaster dalam lingkup tata ruang kawasan. Metode penelitian secara studi kasus yang bersifat induktif-kualitatif eksploratif. Pola konseptual inilah yang akan dikembangkan menjadi model di kawasan-kawasan lereng gunungapi lainnya.
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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) | 0.001 | 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) | 0.013 | 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".