Predictions of Food Security Based on Land Requirements in Sukoharjo Regency in 2032
Bibliographic record
Abstract
Urbanisasi memberikan banyak dampak pada suatu wilayah salah satunya adalah terjadinya fenomena urban Sprawl yang berdampak pada wilayah pinggiran kota. Kabupaten Sukoharjo sebagai salah satu Wilayah Peri Urban (WPU) yang terdampak dari perkembangan Kota Surakarta mengalami peningkatan jumlah penduduk dan diproyeksikan akan terus meningkat sampai tahun 2032. Hal ini menyebabkan semakin sempitnya lahan pertanian yang akan berdampak pada tingkat ketahanan pangan di wilayah tersebut. Melalui proyeksi penduduk dan pemodelan penggunaan lahan tahun 2032 berbasis cellular automata dilakukan perhitungan kebutuhan lahan setara beras sebagai upaya untuk memprediksi tingkat ketahanan pangan Kabupaten Sukoharjo di tahun 2032 mendatang. Berdasarkan hasil perhitungan diketahui bahwa tingkat ketahanan pangan Kabupaten Sukoharjo tahun 2032 diprediksi akan mengalami defisit pangan diseluruh Kecamatan, kondisi ini tentunya memerlukan perhatian khusus dari pemerintah sebagai upaya prefentif agar ketahanan pangan di Kabupaten Sukoharjo tetap terjaga dan dapat mencapai tingkat swasembada pangan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".