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Record W4405687886 · doi:10.33658/jl.v20i2.410

Strategi Penanganan Kawasan Permukiman Kumuh Pesisir Pekalongan melalui Mitigasi Bencana dan Pembangunan Berkelanjutan

2024· article· en· W4405687886 on OpenAlexaff
Widi Hari Nugroho, Bachtiar Yudiana

Bibliographic record

VenueJurnal Litbang Media Informasi Penelitian Pengembangan dan IPTEK · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

ENGLISHTidal flooding is a climate change impact in the northern region of Java, including Pekalongan Regency. Tidal flooding in Pekalongan Regency takes place every year and it is difficult to handle because simultaneously with land subsidence and rising sea levels due to global warming. Tidal flooding is related to the level of slum settlements, especially in Wonokerto District. Wonokerto residents who are submerged by tidal floods tend to stay and adapt to existing environmental conditions rather than migrate to other locations. This study analyzed the strategy for handling slum settlements in coastal communities of Pekalongan Regency that have adapted to tidal floods. This study used mixed methods between qualitative and quantitative descriptive methods through SWOT and a strategic planning approach that processes the results of field observations, citizen interviews and literature studies of regional policies. This study integrates disaster mitigation and sustainable development aspects to build community resilience and produces 14 proposed strategies that must involve all relevant stakeholders, namely the Government; Wonokerto Community; and active Institutions/Organizations in the environmental, social and health fields to support the achievement of program goals and benefits. INDONESIABanjir rob merupakan dampak perubahan iklim di wilayah utara Jawa, salah satunya Kabupaten Pekalongan. Banjir rob di Kabupaten Pekalongan terus terjadi setiap tahunnya dan sulit ditangani karena berjalan bersamaan dengan penurunan muka tanah serta peningkatan muka air laut akibat pemanasan global. Banjir rob berdampingan erat dengan tingkat kekumuhan permukiman terutama di Kecamatan Wonokerto. Masyarakat Wonokerto yang terendam banjir rob cenderung tetap tinggal dan beradaptasi dengan kondisi lingkungan yang ada dibanding bermigrasi ke lokasi lain. Penelitian ini bertujuan menganalisis strategi penanganan permukiman kumuh pada masyarakat pesisir Kabupaten Pekalongan yang telah beradaptasi dengan banjir rob. Penelitian ini menggunakan metode campuran antara deskriptif kualitatif dan kuantitatif melalui SWOT dan pendekatan strategic planning yang mengolah hasil observasi lapangan, wawancara warga dan studi pustaka kebijakan daerah. Penelitian ini mengintegrasikan aspek mitigasi bencana dan pembangunan berkelanjutan guna membangun ketahanan komunitas dan menghasilkan 14 usulan strategi yang harus melibatkan seluruh stakeholder terkait yaitu Pemerintah; Masyarakat Wonokerto; serta Lembaga/Organisasi aktif di bidang lingkungan, sosial maupun kesehatan guna mendukung ketercapaian tujuan dan manfaat program.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.002

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 head0.018
GPT teacher head0.283
Teacher spread0.265 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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