Evaluasi Kesesuaian Lahan Tanaman Jati Pada Bekas Tambang di Dusun Girigondo, Kalurahan Kaligintung, Kapanewon Temon, Kabupaten Kulon Progo, D.I. Yogyakarta
Bibliographic record
Abstract
Kegiatan Pertambangan di Dusun Girigondo, Kalurahan Kaligintung, Kapanewon Temon, Kabupaten Kulon Progo, Daerah Istimewa Yogyakarta ditinggalkan tanpa melakukan pengelolaan sehingga memunculkan kerusakan lingkungan dan tidak produktifnya suatu lahan. Penelitian ini dilakukan guna mengetahui dan mengevaluasi kesesuaian lahan peruntukan tanaman jati pada lahan bekas pertambangan. Metode yang digunakan dalam penelitian yaitu (1) metode survei dan pemetaan, (2) metode purposive sampling berdasarkan satuan medan, (3) analisis laboratorium, (4) metode matching. Parameter yang digunakan untuk evaluasi kesesuaian lahan yaitu : Temperatur (t), Lama bulan kering (bk), Curah Hujan/Tahun (ch), Drainase/Permeabilitas (d), Tekstur (tt), Kedalaman Tanah (kt), pH Tanah (ph), Salinitas (s), Batuan di permukaan (bd), Singkapan Batuan (sb), Bahaya Erosi (be), Kemiringan Lereng (kl), Bahaya Banjir (bb). Hasil evaluasi kesesuaian lahan bekas tambang untuk tanaman jati menunjukkan bahwa semua satuan medan tergolong dalam kelas N2 (tidak sesuai selamanya) dengan faktor pembatas secara keseluruhan berupa d, kt, bd, sb, be, kl.Kata Kunci: Lahan Bekas Pertambangan; Kerusakan Lingkungan; Evaluasi Lahan; Kesesuaian Lahan; Tanaman Jati
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".