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Record W2768755066 · doi:10.33751/teknik.v16i1.356

ANALISIS LAHAN KRITIS KECAMATAN BOGOR TIMUR, KOTA BOGOR, JAWA BARAT

2015· article· id· W2768755066 on OpenAlexaff
Helmi Setia Ritma Pamungkas, Muhammad Agus Karmadi

Bibliographic record

VenueJurnal Teknik | Majalah Ilmiah Fakultas Teknik UNPAK · 2015
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsForestryGeography

Abstract

fetched live from OpenAlex

Untuk menuju kota berkelanjutan, maka perlu upaya rehabilitasi lahan kritis menjadi lebih hijau dan bermanfaat bagi warga sekitar. Kota Bogor sendiri ditetapkan sebagai kawasan hulu, dan menjadi penyangga kawasan ibukota dan kota-kota di bawahnya, sebagai daerah resapan air, dan daerah konservasi menurut Peraturan Presiden tahun 2008 tentang Penataan Ruang Kawasan Jabodetabekpunjur. Sebelum adanya pelaksanaan penanggulangan lahan kritis, maka perlu ada upaya identifikasi lahan kritis yang berada di Kota Bogor, terutama di Kecamatan Bogor Timur. Metodologi penentuan lahan kritis berdasarkan Peraturan Menteri Kehutanan Nomor. P.32/Menhut-II/2009 tentang Tata Cara Penyusunan Rencana Teknik Rehabilitasi Hutan dan Lahan Daerah Daerah Aliran Sungai (RTKRHL-DAS). Berdasarkan hasil penelitian, kategori kawasan budidaya untuk pertanian didapatkan luasan lahan kritis yaitu 98,21 ha dan luas lahan agak kritis 111,2 ha; dan kategori kawasan lindung didapatkan luasan lahan sangat kritis yaitu 7,99 ha, kritis seluas 18,94 ha, dan luas lahan agak kritis 3,2 ha. Nilai dukungan apek sosial ekonomi yakni 11,06 yang berarti kurang.Kata Kunci : Lahan Kritis, Bogor Timur

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.029
GPT teacher head0.238
Teacher spread0.209 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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