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Record W4395093057 · doi:10.29313/bcsurp.v4i1.11588

Resiliensi Masyarakat terhadap Banjir di Kecamatan Gedebage Kota Bandung

2024· article· en· W4395093057 on OpenAlexaff
Fiqri Yuda Perdana, Ira Safitri Darwin

Bibliographic record

VenueBandung Conference Series Urban & Regional Planning · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsEncana (Canada)
FundersUniversitas Islam Bandung
KeywordsPsychology

Abstract

fetched live from OpenAlex

Abstract. Flooding has become an ongoing challenge for communities in various regions, including in Gedebage Sub-district, Bandung City. This study aims to determine the addition of flood areas and the level of community resilience in facing floods with the BRACED variable criteria. The research methods used were quantitative and qualitative. The results showed that there was an increase in the flood area in Gedebage Sub-district from 2015-2021 in two urban villages, namely Rancanumpang and Cimincrang due to the development of the Gedebage Technopolis concept, and the level of community resilience to flooding was in the low category. This research underscores the importance of collaboration between the government, related institutions and communities in building resilience to flood disasters. Joint efforts to improve knowledge, strengthen infrastructure, and facilitate access to relevant information will be key in improving community resilience to floods in Gedebage Sub-district, Bandung City. Abstrak. Bencana banjir telah menjadi tantangan yang berkelanjutan bagi masyarakat di berbagai wilayah, termasuk di Kecamatan Gedebage, Kota Bandung. Penelitian ini bertujuan untuk mengetahui penambahan wilayah luas banjir dan tingkat resiliensi masyarakat dalam menghadapi banjir dengan kriteria variabel BRACED. Metode penelitian yang digunakan adalah kuantitatif dan kualitatif. Hasil penelitian menunjukkan bahwa terjadi penambahan luas banjir di Kecamatan Gedebage dari tahun 2015-2021 di dua Kelurahan, yaitu Rancanumpang dan Cimincrang karena adanya pembangunan konsep Teknopolis Gedebage, dan tingkat resiliensi masyarakat terhadap banjir termasuk dalam kategori rendah. Penelitian ini menggaris bawahi pentingnya kolaborasi antara pemerintah, lembaga terkait, dan masyarakat dalam membangun resiliensi terhadap bencana banjir. Upaya bersama untuk meningkatkan pengetahuan, memperkuat infrastruktur, dan memfasilitasi akses terhadap informasi yang relevan akan menjadi kunci dalam meningkatkan resiliensi masyarakat terhadap bencana banjir di Kecamatan Gedebage, Kota Bandung.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.235
Teacher spread0.211 · 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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