MétaCan
Menu
Back to cohort
Record W4408495030 · doi:10.70305/jmdm.v1i2.89

SOSIALISASI KESIAP SIAGAAN TERHADAP ERUPSI GUNUNG BROMO KEPADA PELAKU WISATA DAN MASYARAKAT

2024· article· id· W4408495030 on OpenAlexaff
Khusnik Hudzafidah, Saiful Bahri, Wahyu Andrian Kusuma

Bibliographic record

VenueJurnal Mitra Dedikasi Masyarakat · 2024
Typearticle
Languageid
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Indonesia, sebagai negara kepulauan terbesar di dunia yang terletak di sepanjang Cincin Api Pasifik, sangat rentan terhadap berbagai bencana geologi seperti gempa bumi, tsunami, dan letusan gunung berapi. Salah satu gunung berapi aktif yang terkenal di Indonesia adalah Gunung Bromo, yang menjadi tujuan wisata populer namun juga menyimpan potensi bahaya erupsi. Penelitian ini bertujuan untuk menilai efektivitas program sosialisasi yang dilakukan oleh Pusat Vulkanologi dan Mitigasi Bencana Geologi (PVMBG) dalam meningkatkan kesadaran masyarakat dan pelaku wisata di sekitar Gunung Bromo tentang mitigasi bencana. Metode penelitian yang digunakan adalah penelitian tindakan sosial dengan melibatkan total 70 responden yang terdiri dari pemangku kepentingan dan masyarakat lokal. Program sosialisasi mencakup seminar, lokakarya, dan simulasi kesiapsiagaan bencana. Hasil penelitian menunjukkan adanya peningkatan pemahaman tentang mitigasi bencana, dengan peningkatan rata-rata sebesar 7.5% di kalangan pemerintah dan 19.45% di kalangan non-pemerintah. Penelitian ini menyimpulkan bahwa sosialisasi yang rutin dan berkelanjutan penting dilakukan untuk meningkatkan kesiapsiagaan bencana dan meminimalisir risiko bencana di masa depan.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.003
Science and technology studies0.0040.002
Scholarly communication0.0040.002
Open science0.0030.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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; both teacher heads agree on what is shown here.

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

Explore more

Same venueJurnal Mitra Dedikasi MasyarakatSame topicCommunity-based Tourism Development and SustainabilityFrench-language works237,207