MétaCan
Menu
Back to cohort

DAMPAK ABRASI TERHADAP LINGKUNGAN DAN SOSIAL BUDAYA DI WILAYAH PESISIR PANTAI PABEAN, GIANYAR

2021· article· id· W3204817688 on OpenAlexaff
Made Ratna Witari, Agus Wiryadhi Saidi, Komang Sariasih

Bibliographic record

VenueJurnal Teknik Gradien · 2021
Typearticle
Languageid
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesArt

Abstract

fetched live from OpenAlex

Wilayah pesisir merupakan daerah peralihan antara ekosistem darat dan laut yang memiliki berbagai potensi sumber daya alam. Namun meningkatnya laju abrasi menjadi ancaman bagi wilayah pesisir saat ini. Abrasi ialah pengikisan daratan akibat aktivitas gelombang, arus maupun pasang surut laut yang dapat menyebabkan berubahnya garis pantai. Salah satu Pantai yang terkena dampak abrasi ialah Pantai Pabean yang berada di Desa Ketewel, Kecamatan Sukawati, Gianyar. Pantai Pabean memiliki suasana tenang dan jauh dari hiruk pikuk kota menjadikan pantai ini kian diminati wisatawan. Akan tetapi, berkembangnya kawasan Pantai Pabean tegak lurus dengan kerusakan pesisir akibat abrasi yang semakin parah. Tujuan Penelitian ini ialah untuk mengkaji dampak abrasi terhadap lingkungan dan sosial budaya di wilayah pesisir Pantai Pabean serta upaya yang telah dilakukan untuk menahan laju abrasi pada tahun 2018. Penelitian ini menggunakan metode kualitatif dengan pendekatan historis untuk dapat menggambarkan kebenaran di masa lalu. Data diuraikan secara deskriptif dengan disertakan data pendukung seperti peta dan gambar. Pengumpulan data dilakukan dengan cara observasi, wawancara dan studi literatur. Hasil akhir penelitian menunjukkan bahwa telah banyak terjadi perubahan lingkungan dan sosial budaya masyarakat di pesisir Pantai Pabean akibat abrasi yang diuraikan menjadi empat bagian, yaitu : (1) Hilangnya persil tanah di sepanjang pesisir Pantai Pabean; (2) Pindahnya lokasi pelaksanaan kegiatan upacara agama melasti; (3) Bergesernya mata pencaharian masyarakat; (4) Sampah yang menumpuk di Pesisir Pantai Pabean. Langkah yang sudah dilakukan untuk mengurangi dampak abrasi ialah dengan mitigasi struktural berupa pembangunan talud.

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 score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0250.006

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 head0.013
GPT teacher head0.224
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 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Teknik GradienSame topicCoastal Management and DevelopmentFrench-language works237,207