KAJIAN RISIKO BENCANA LONGSOR KECAMATAN LOANO KABUPATEN PURWOREJO
Bibliographic record
Abstract
Kecamatan Loano berada di bagian timur-selatan Kabupaten Purworejo, merupakan daerah rawan longsor yang disertai kondisi sosial ekonomi yang menambah kerentanannya. Studi ini bertujuan untuk mengkaji risiko bencana longsor, cakupan kajian meliputi karakteristik ancaman, kerentanan {sosial ekonomi & fisik lingkungan, kapasitas (respon lingkungan)} serta risiko bencana. Pengolahan data menggunakan software ArcGIS dan SPSS. Secara fisik alam, ancaman risiko longsor bervariasi yaitu 21,36 km2 (40,09%) indeks rendah, 13.14 km2 (24,66%) sedang dan 18,78 km2 (35,25%) tinggi. Indeks kerentanan sosial ekonomi & fisik lingkungan terdiri dari 3 desa indeks rendah, 11 desa sedang dan 7 desa tinggi. Karakteristik kapasitas (respon lingkungan) diambil dengan menggunakan kuesioner individu masyarakat dan pemerintah desa. Karakteristik kapasitas (respon lingkugan)-nya adalah 14 desa indeks rendah, 4 desa sedang dan 3 desa tinggi. Kerentanan secara holistickyang merupakan jumlah total kerentanan sosial ekonomi & fisik lingkungan serta kapasitas (respon lingkungan) terdapat 3 desa indeks rendah, 4 desa sedang dan 14 desa tinggi. Tingkat risiko bencana longsor bervariasi, terdiri dari rendah 6,72 km2 (12,62%) , sedang 24,59 km2 (46,15%) hingga tinggi 21,96 km2 (41,23%). Risiko longsor yang tinggi perlu dikurangi dengan menurunkan kerentananya. Selanjutnya, diharapkan metode ini dapat diterapkan di wilayah lainnya yang memiliki karakteristik hampir sama dengan Kecamatan Loano.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.018 |
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; both teacher heads agree on what is shown here.
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".