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Record W4402279508 · doi:10.36985/bqbvxb40

Analisis Spasial Kesesuaian Fungsi Kawasan Daerah Aliran Sungai Tungka Dengan Rencana Tata Ruang Wilayah Kabupaten Tapanuli Tengah

2024· article· id· W4402279508 on OpenAlexaff
Ronal Richard Haposan Sibuea, Ummu Harmain, Simon H Sidabukke

Bibliographic record

VenueJurnal Regional Planning · 2024
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk mengidentifikasi kondisi resapan kawasan DAS Tungka terhadap RTRW Kabupaten Tapanuli Tengah dimana penggunaan lahan dan dinamika yang sangat pesat di Kecamatan Pandan dan Tukka mengindikasikan ketidaksesuaian penggunaan lahan terhadap Rencana Tata Ruang Wilayah (RTRW) Kabupaten Tapanuli Tengah. Penelitian ini menggunakan pendekatan deskriptif kuantitatif yang menggunakan pengumpulan data seperti wawancara, survey lapangan dan dan studi pustaka terkait kondisi umum lokasi penelitian. Hasil analisis identifikasi sebaran daerah resapan pada kawasan DAS Tungka Kabupaten Tapanuli Tengah deskripsi baik pada tahun 2014 sebesar 5.151,60 Ha sedangkan pada tahun 2021 sebesar 4.849,06 Ha, normal alami pada tahun 2014 sebesar 910,54 Ha sedangkan pada tahun 2021 sebesar 736,93 Ha, mulai kritis pada tahun 2014 sebesar 482,50 Ha sedangkan pada tahun 2021 sebesar 483,39 Ha, agak kritis pada tahun 2014 sebesar sebesar 390,36 Ha sedangkan pada tahun 2021 sebesar 573,60 Ha, kritis pada tahun 2014 sebesar249,90 sedangkan pada tahun 2021 sebesar 541,92 Ha dan sangat kritis pada tahun 2014 sebesar 0,00 Ha sedangkan pada tahun 2021 sebesar 0,00 Ha. Hasil analisis identifikasi tingkat kesesuaian fungsi kawasan eksisting terhadap RTRW Kabupaten Tapanuli Tengah pada hutan lindung sebesar 971,54 Ha atau 91 %, perkebunan sebesar 79,90 Ha atau 21 %, permukiman sebesar 633,25 Ha atau 74 %, pertanian sebesar 131,45 Ha atau 22 %, hutan produksi sebesar 3.500,94 Ha atau 98 %, sempadan sungai sebesar 412,40 Ha atau 60 %, air sungai sebesar 21,76 Ha atau 59 %, tingkat kesesuaian terhadap semua pola ruang adalah 80 %.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.071
GPT teacher head0.270
Teacher spread0.199 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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