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Record W4403238954 · doi:10.29313/bcsurp.v4i3.15364

Partisipasi Masyarakat dalam Penanggulangan Banjir di Kecamatan Periuk

2024· article· en· W4403238954 on OpenAlexaff
Rani Indah Sri Safitri, Yulia Asyiawati

Bibliographic record

VenueBandung Conference Series Urban & Regional Planning · 2024
Typearticle
Languageen
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Abstract. Floods are one of the most frequent natural disasters in Indonesia, especially in lowland and urban areas, as is the case in Priuk District, Tangerang City. Physically, this sub-district is a type of lowland, which is crossed by 3 rivers including Kali Sabi, Kali Ledug, and Kali Cirarab, as well as 2 lakes, namely Bulakan and Cangkring. Conditions are one of the factors that cause flooding. The impact of flood events with a height of 5 cm - 2 meters has a detrimental impact on the community. Community participation is a key element in sustainable and effective flood management efforts. The aim of this research is to identify the type and level of community participation in flood management in Periuk District. Through the descriptive analysis method, it was found that flooding occurred in each sub-district with different durations, which resulted in damage to infrastructure, with estimated community losses of IDR 5.6 billion. Communities affected by floods have participated in dealing with floods, with the types of participation carried out being property, energy and social. The level of community participation in dealing with floods in this sub-district includes self-management, consensus-building and manipulation. Based on these findings, it can be concluded that the type of participation carried out by the community in flood areas is property with a consensus-building level of participation. Sub-districts that were not affected by flooding provided participation in the form of personnel, with manipulation of participation levels. This research recommends strengthening community participation mechanisms through inclusive policies and sustainable education to create an environment that is more resilient to flood disasters. Abstrak. Banjir merupakan salah satu bencana alam yang paling sering terjadi di Indonesia, terutama di daerah dataran rendah dan perkotaan, begitu juga halnya dengan Kecamatan Priuk, Kota Tangerang. Secara fisik kecamatan ini merupaka dataran rendah dengan jenis, yang dilewati oleh 3 sungai meliputi Kali Sabi, Kali Ledug, dan Kali Cirarab, serta 2 situ, yaitu Bulakan dan Cangkring. Kondisi salah satu faktor yang menyebabkan terjadinya banjir, Dampak dari kejadian banjir dengan ketinggian 5 cm – 2 mater memberikan dampak kerugian bagi masyarakat. Partisipasi masyarakat merupakan elemen kunci dalam upaya penanggulangan banjir yang berkelanjutan dan efektif. Tujuan dari penelitian ini adalah mengidentifikasi jenis dan tingkat partisipasi masyarakat dalam penanganan banjir di Kecamatan Periuk. Melalui metode analisis deskriptif ditemukan bahwa banjir terjadi disetiap kelurahan dengan durasi yang berbeda-beda, yang memberikan dampak kerusakan infrastruktur, yang diperkirakan kerugian masyarakat adalah sebesar Rp 5,6 Miliar. Masyarakat yang terdampak banjir sudah berpartisipasi untuk menangani banjir, dengan jenis partisipasi yang dilakukan adalah Harta benda, tenaga dan sosial, Tingkat partisipasi masyarakat dalam menangani banjir di kecamatan ini meliputi self-management, consensus-building dan Manipulation. Berdasarkan temuan ini dapat disimpulkan bahwa jenis partisipasi yang dilakukan masyarakat pada kawasan banjir adalah harta benda dengan tingkat partisipasi consensus-building. Kelurahan yang tidak terdampak banjir memberikan partisipasi berupa tenaga , dengan tingkat partisipasi manipulation Penelitian ini merekomendasikan penguatan mekanisme partisipasi masyarakat melalui kebijakan inklusif dan edukasi berkelanjutan guna menciptakan lingkungan yang lebih tangguh terhadap bencana banjir.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.039
GPT teacher head0.269
Teacher spread0.230 · 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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