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Record W4403239117 · doi:10.29313/bcsurp.v4i3.14734

Identifikasi Faktor-Faktor Penyebab Urban Sprawl di Kecamatan Cileunyi

2024· article· en· W4403239117 on OpenAlexaff
Salsabila Nurrizki, Tarlani, Ira Safitri Darwin

Bibliographic record

VenueBandung Conference Series Urban & Regional Planning · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsUrban sprawlEngineeringUrban planningCivil engineering

Abstract

fetched live from OpenAlex

Abstract. Cileunyi District, which is flanked by Bandung City and Sumedang Regency, is currently experiencing rapid development from all directions. Cileunyi District is developing due to its direct border with Bandung City in the west, then in the east it borders Jatinangor District which is an educational area, in the south it borders Bojongsoang District which is planned as a new city precisely in Tegalluar Village and borders Rancaekek District which is an industrial area. Cileunyi District in the Bandung Regency RTRW is included in the National Strategic Area Development (KSN) plan, namely the Bandung Basin Urban Area, this has caused Cileunyi District to experience the spread of built-up land (urban sprawl). so that it is feared that it will have an impact on congestion, environmental damage, and social change. This study aims to identify the factors causing urban sprawl in Cileunyi District due to the rapid development that occurs in various corners around Cileunyi District. The method used in this study is multiple linear regression analysis. In this study, the identification of factors causing urban sprawl in Cileunyi District was carried out, using multiple linear regression analysis with an error of 5%. The results showed that simultaneously there were 9 variables that had a significant effect on urban sprawl, namely accessibility, public services, economic conditions, spatial planning regulations, views, migration, land value, physical characteristics of the land, and developer initiatives. Abstrak. Kecamatan Cileunyi yang di apit oleh Kota Bandung dan Kabupaten Sumedang saat ini mengalami perkembangan cepat dari segala penjuru, Kecamatan Cileunyi berkembang akibat berbatasan langsung dengan Kota Bandung pada bagian barat, lalu pada bagian timur berbatasan dengan Kecamatan Jatinangor yang merupakan kawasan pendidikan, pada bagian selatan berbatasan dengan Kecamatan Bojongsoang yang di rencanakan sebagai kota baru tepatnya di Desa Tegalluar serta berbatasan dengan Kecamatan Rancaekek yang merupakan kawasan industri. Kecamatan Cileunyi pada RTRW Kabupaten Bandung masuk dalam rencana Pengembangan Kawasan Strategis Nasional (KSN) yaitu Kawasan Perkotaan Cekungan Bandung, hal tersebut mengakibatkan Kecamatan Cileunyi mengalami perembetan lahan terbangun (urban sprawl). sehingga dikhawatirkan berdampak pada kemacetan, kerusakan lingkungan, dan perubahan sosial. Studi ini bertujuan untuk mengidentifikasi faktor-faktor penyebab urban sprawl di Kecamatan Cileunyi akibat dari perkembangan cepat yang terjadi di berbagai penjuru sekeliling Kecamatan Cileunyi. Metode yang digunakan dalam penelitian ini adalah analisis regresi linear berganda. Pada penelitian ini dilakukan identifikasi faktor-faktor penyebab urban sprawl di Kecamatan Cileunyi, menggunakan analisis regresi linear berganda dengan error 5%, hasilnya menunjukkan bahwa secara simultan terdapat 9 variabel yang berpengaruh signifikan terhadap urban sprawl, yaitu aksesibilitas, pelayanan umum, kondisi ekonomi, peraturan tata ruang, pemandangan, migrasi, nilai lahan, karakteristik fisik lahan, dan prakarsa pengembang.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.057
GPT teacher head0.241
Teacher spread0.184 · 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 teacher head, not a consensus.

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
Published2024
Admission routes1
Has abstractyes

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