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Record W4391363268 · doi:10.35315/dinamik.v29i1.9370

Analisis Kesesuaian Lahan Untuk Pengembangan Kawasan Industri Di Provinsi Jawa Barat

2024· article· id· W4391363268 on OpenAlex

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

VenueDinamik · 2024
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsEnvironmental scienceForestryGeography

Abstract

fetched live from OpenAlex

Pengembangan kawasan industri di Jawa Barat perlu pembangunan yang memperhatikan kesesuaian lahan agar tidak memberikan masalah bagi lingkungan dan keberlanjutan ekologi. Oleh karena itu, perlu dilakukan analisis kesesuaian lahan untuk pengembangan kawasan industri dengan melihat Satuan Kemampuan Lahan (SKL). Hasil evaluasi SKL menunjukkan bahwa Provinsi Jawa Barat bagian utara memiliki tingkat kesesuaian lahan yang paling baik untuk pengembangan kawasan industri untuk jenis SKL bencana alam, erosi, pembuangan limbah, morfologi, kestabilan pondasi, kestabilan lereng, dan kemudahan pengembangan. Sementara itu, hasil analisis kesesuaian kawasan industri menunjukkan bahwa 33,31% dari total luas wilayah Provinsi Jawa Barat sesuai untuk pengembangan kawasan industri dengan sebaran spasial di bagian utara Provinsi Jawa Barat, 61,99% kurang sesuai, dan 1,70% masuk dalam kategori tidak sesuai. Perbandingan hasil analisis kesesuaian lahan dengan RTRW Jawa Barat juga menunjukkan rencana industri di utara pulau masuk dalam kategori sesuai untuk pengembangan industri, sedangkan rencana industri di tengah dan selatan pulau masuk dalam kategori kurang sesuai.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.032
GPT teacher head0.230
Teacher spread0.198 · 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