PENERAPAN METODE PENGEMBANGAN LAHAN (LAND DEVELOPMENT ANALYSIS) DALAM PENILAIAN TANAH
Bibliographic record
Abstract
Keberadaan lahan kosong di lokasi yang cukup potensial akan memberikan nilai tambah bagi pemiliknya jika dilakukan optimalisasi atas lahan kosong dimaksud. Penentuan nilai tanah kosong seluas 36.640 m2 di lingkungan permukiman tidak memungkinkan menggunakan pendekatan pasar, sehingga dipilih pendekatan pendapatan dengan metode Land Development Analysis , yang diasumsikan hamparan tanah tersebut dapat dikembangkan menjadi kawasan permukiman sebagai alternatif penggunaan terbaik dan tertinggi. Berdasarkan rencana pengembangan lahan, nilai pasar tanah diperoleh dari arus kas yang berasal dari pendapatan penjualan unit rumah dikurangi dengan biaya pengembangan atas lahan tersebut Dari hasil analisis diperoleh indikasi nilai pasar tanah sebesar Rp3.500.891,50
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".