STRATEGI BPBD KABUPATEN PACITAN DALAM UPAYA PENANGGULANGAN BENCANA BANJIR DAN TANAH LONGSOR
Bibliographic record
Abstract
This study aims to determine the condition of natural disasters such as floods and landslides and the efforts of BPBD to overcome them. The research was conducted in Pacitan City on the basis of the consideration that floods and landslides are common in this area. Data was collected through open interviews, observation, and document review, then the data were analyzed descriptively qualitatively. The results showed that the condition of the Pacitan City area consists mostly of highlands in the form of steep mountains and shallow river areas so that it is very vulnerable to natural disasters in the form of floods and landslides, especially during the rainy season. The flood natural disaster that occurred in Pacitan City was mainly caused by the silting of the riverbed and the narrowing of the river's width. Meanwhile, landslides are caused by erosion caused by rainwater and the increasing number of residential areas that make the foot of the slope increasingly eroded. Efforts made by BPBD to overcome natural disasters of floods and landslides that occurred in Pacitan Regency were by launching various forms of strategies such as the DESTANA program, Socialization, Procurement of Disaster Simulations, Construction of Embankments, Installation of Information Signs for Disaster-Prone Areas, Map-making of Disaster-Prone Areas and Determination of Evacuation Areas, and Mangrove Planting. The various strategies implemented also serve to increase public awareness and preparedness for disasters.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".