Evaluasi Lereng Bekas Tambang Pasir dan Batu Berdasarkan Nilai Faktor Keamanan di Dusun Tawang, Desa Sidorejo, Kecamatan Kemalang, Kabupaten Klaten
Bibliographic record
Abstract
Dusun Tawang, Desa Sidorejo, Kecamatan Kemalang, Kabupaten Klaten merupakan salah satu lokasi kegiatan pertambangan pasir dan batuan yang sudah dimulai sejak 2006. Kegiatan tersebut meninggalkan lereng yang tidak diperbaiki sehingga memiliki ancaman gerakan massa tanah dan/atau batuan. Desa Sidorejo juga sudah ditetapkan sebagai daerah rawan longsor dengan potensi tinggi pada bulan Desember 2018 oleh Pusat Vulkanologi dan Mitigasi Bencana Geologi. Penelitian ini dilakukan dengan tujuan mengetahui dan mengevaluasi kondisi eksisting lereng tambang menggunakan nilai faktor keamanan pada lereng bekas tambang. Metode yang digunakan yaitu studi literatur, survei lapangan dan pemetaan fisik lingkungan, serta metode uji laboratorium. Teknik analisis data dilakukan dengan menggunakan Metode Spencer dan Metode Analisis Deskriptif untuk mengevaluasi lereng bekas tambang terhadap gerakan massa tanah dan/atau batuan. Hasil penelitian menunjukkan bahwa gerakan massa tanah/batuan yang ada berupa keruntuhan permukaan lereng. Nilai faktor keamanan lereng sebesar 0,603 pada lereng 1; 0,799 pada lereng 2; dan 0,341 pada lereng 3. Ketiga lereng termasuk ke dalam kategori lereng tidak stabil.Kata Kunci: Evaluasi, Gerakan massa, Lereng, Bekas Tambang, Faktor Keamanan
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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 | 0.003 | 0.002 |
| 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 | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".