MétaCan
Menu
Back to cohort
Record W4412467595 · doi:10.22487/peweka.v2i1.10

Kesesuaian Kegiatan Pemanfaatan Ruang Pada Kawasan Lindung di Kota Palu

2023· article· id· W4412467595 on OpenAlexaff
Rizkhi Rizkhi, Vivi Novianti, Fitriah Fajar Magfirah, Fadila Ramadhani

Bibliographic record

VenueJurnal PeWeKa Tadulako · 2023
Typearticle
Languageid
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Pengembangan atau pembangunan suatu wilayah harus berdasar pada lahan yang tersedia, karena lahan merupakan sumberdaya utama yang sangat dibutuhkan. Pengembangan atau pembangunan di Kota Palu terlihat pada penggunaan lahan yang makin berkembang dan dinamis, sehingga perlu terus dipantau perkembangannya karena seringkali pemanfaatan lahan tidak sesuai dengan peruntukannya, hal tersebut akan menyebabkan daya dukung lingkungan terlampaui. Kondisi ini mengisyaratkan bahwa untuk mewujudkan terciptanya pemanfaatan ruang yang “tertib ruang” diperlukan tindakan pengendalian pemanfaatan ruang yang sungguh-sungguh. Sehingga perlunya tindakan pengkajian tingkat kesesuaian pemanfaatan ruang di Kota Palu. Penyimpangan pemanfaatan lahan pada Kawasan lindung di Kota Palu, Teridentifikasi Kawasan Permukiman yang masuk dalam area sempadan pantai seluas 62,69 Ha, Permukiman masuk dalam area sempadan sungai 37,12 Ha, Permukiman yang masuk dalam area ruang terbuka seluas 47,32 ha, dan permukiamn masuk dalam area patahan aktif seluas 7,31 Ha. Berdasarkan kondisi yang ada, penelitian ini di lakukan untuk mengetahui tingkat efektifitas pemanfaatan ruang pada Kawasan lindung di Kota Palu berdasarkan tingkat kesesuaian pemanfaatan ruang yang tertuang dalam rencana tata ruang yang ada, dengan sasaran mengkaji perkembangan Penggunaan lahan 2019 hingga 2021, mengkaji kesesuaian dan deviasi pemanfaatan ruang yang terjadi pada Kawasan lindung di Kota Palu.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJurnal PeWeKa TadulakoSame topicGeotechnical and construction materials studiesFrench-language works237,207