ANALISIS MITIGASI BENCANA ALAM DENGAN PENDEKATAN SISTEM INFORMASI GEOGRAFIS DI MAGELANG
Bibliographic record
Abstract
Secara geografis Magelang terletak antara 110001’51” dan 110026’58” Bujur Timur dan antara 7019’13” dan 7042’16” Lintang Selatan. Secara administratif, terbagi ke dalam 13 Kecamatan. Topografi Karisidenan Kedu secara umum merupakan dataran tinggi yang berbentuk basin (cekungan). Diapit oleh gunung Merbabu, Merapi, Andong, Telomoyo, Sumbing dan Pegunungan Menoreh,dengan dua sungai besar yang mengalir ditengahnya yaitu sungai Progodan dan sungai Elo. Tersusun dari formasi batuan Andesit tua dengan jenis tanah Aluvial, Regosol dan Latosol. Tingkat kemiringan lereng yang cukup curam dan dengan kondisi jenis tanah yang ada di Magelang dapat memicu kerentanan bencana alam. Tingkat curah hujan yang cukup tinggi dapat memicu bencana tanah longsor didaerah pegunungan dan lereng gunung, sedangkan di daerah yang lebih rendah terjadi bencana banjir. Oleh karena itu, berangkat dari factor internal dan eksternal tersebut maka diperlukan analisis mitigasi bencana geologi dengan pendekatan SIG dalam meminimalisir korban harta dan jiwa.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 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".