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Record W4387432610 · doi:10.59004/jisma.v2i4.430

PENERAPAN METODE PENGEMBANGAN LAHAN (LAND DEVELOPMENT ANALYSIS) DALAM PENILAIAN TANAH

2023· article· id· W4387432610 on OpenAlex
Petrus Teguh Subagyo, Nurhidayah Nurhidayah

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJISMA Jurnal Ilmu Sosial Manajemen dan Akuntansi · 2023
Typearticle
Languageid
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysicsHydrology (agriculture)ForestryEnvironmental scienceEngineeringGeographyGeotechnical engineering

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.005

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.

Opus teacher head0.016
GPT teacher head0.236
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it