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Record W4413332798 · doi:10.29313/bcsurp.v5i2.20362

Tingkat Resiliensi Masyarakat dalam Menghadapi Banjir Rob di Kawasan Pesisir Eretan Kabupaten Indramayu

2025· article· en· W4413332798 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBandung Conference Series Urban & Regional Planning · 2025
Typearticle
Languageen
FieldComputer Science
TopicData Mining and Machine Learning Applications
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

Abstract. The community affected by the tidal flood has started to adapt to their environment and find various ways to cope to survive in areas impacted by the tidal flood. The tidal flood disaster in the Eretan coastal area has worsened and continues to recur, causing damage not only to physical buildings and infrastructure but also impacting the social and economic activities of the community. The floods also damage access roads and several vehicles, leading the community to implement mitigation efforts by raising house foundations and building door barriers. The aim of this research is to assess the level of resilience of the community against the tidal floods in the Eretan coastal area. To assess the resilience of the community affected by the tidal floods, data sources were collected through questionnaires, document reviews, and observations. The analytical method used is Likert scale analysis with scoring and descriptive analysis. The results of the analysis indicate that the level of resilience of the community in the Eretan Coast is categorized as High at 76% and the sustainability of the lives of the coastal communities in Eretan is also high. This research recommends that the breakwater structure should be optimized and maintained properly, the rehabilitation and expansion of mangrove forests to enhance natural defenses against waves and abrasion should be undertaken, and permanent concrete river retaining walls should be constructed along riverbanks to prevent river overflow into settlements, as well as to create sustainable economic incentives. Abstrak. Masyarakat yang terdampak banjir mulai terbiasa dengan lingkungannya dan mampu mengatasinya dengan berbagai cara untuk tetap bertahan pada kondisi wilayah yang terdampak banjir rob. Bencana banjir rob di kawasan Pesisir Eretan sudah semakin parah dan terus berulang, akibat yang ditimbulkan dari bencana banjir rob tidak hanya merusak fisik bangunan dan infrastruktur, melainkan berdampak pada kegiatan sosial dan ekonomi masyarakat, banjir juga merusak akses jalan dan beberapa kendaraan, serta masyarakatpun melakukan upaya mitigasi dengan meninggikan pondasi rumah dan membangun penghalang pintu. Tujuan dari penelitian ini adalah untuk menilai tingkat resiliensi masyarakat terhadap banjir rob kawasan Pesisir Eretan. Untuk menilai resiliensi masyarakat yang terdampak banjir rob, sumber data dikumpulkan melalui kuesioner, telaah dokumen, dan observasi. Maka metode analisis yang digunakan yaitu analisis skala likert dengan skoring dan deskriptif analisis. Hasil analisis menunjukkan bahwa tingkat resiliensi masyarakat di Pesisir Eretan berada pada kategori Tinggi 76%. Hasil penelitian ini merekomendasikan agar struktur breakwater/pemecah gelombang dioptimalkan dan dipelihara dengan baik, rehabilitasi dan perluasan hutan mangrove untuk meningkatkan pertahanan alami terhadap gelombang dan abrasi, dan membangun dinding penahan sungai berbahan beton permanen di bantaran sungai untuk mencegah luapan air sungai masuk ke permukiman, serta menciptakan insentif ekonomi berkelanjutan.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.775
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.273
Teacher spread0.249 · 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