Pengembangan Sumber Daya Manusia Dalam Manajemen Bencana (Studi Di BPBD Kabupaten Bangka)
Bibliographic record
Abstract
Tujuan dari penelitian ini adalah untuk mengetahui pengembangan sumber daya manusia dalam penanggulangan bencana di Kabupaten Bangka. Menggunakan metode kualitatif bersifat deskriptif yaitu memecahkan masalah secara akurat berdasarkan data-data yang ada. Peneliti menggunakan data yang di kumpulkan dari wawancara dan dokumen. Hasil penelitian ini memperlihatkan bahwa pengembangan informal dengan membaca buku tentang pencegahan terjadinya banjir dan membaca modul dari Badan Meteorologi Klimatologi dan Geofisika (BMKG) yang bertema Kesiapsiagaan menuju zero victim melalui informasi cuaca berbasis dampak dan harus meningkatkan membaca tentang manajemen kedaduratan, manajemen logistik, manajemen rehabilitasi dan manajemen rekonstruksi. Pengembangan formal dengan melakukan bimtek bersama Basarnas Pangkal Pinang tentang melakukan kedaruratan membantu korban tenggelam dan bimtek tentang membantu korban henti detak jantung dan harus meningkatkan diksar dan bimtek tentang manajemen pencegahan, manajemen kesiapsiagaan, manajemen kedaruratan, manajemen rehabilitasi dan manajemen rekonstruksi.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".