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Record W4400745470 · doi:10.59193/jkw.v2i2.251

Media Sosial Sebagai Alat Pemasaran Mangrove Pandang Tak Jemu Di Kampung Tua Bakau Serip

2024· article· en· W4400745470 on OpenAlexaff
Baktivillo Sianipar, Kartika Cahayani, Okta Safitri, Bram Handoko, Dinda Aisyah Nurul Intan, M. Khori Kurnia Subagja, Frangky Silitonga

Bibliographic record

VenueJURNAL KEKER WISATA · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Mangrove Pandang Tak Jemu in Kampung Tua Bakau Serip is a unique and interesting ecotourism destination. Considering the importance of the mangrove tree ecosystem and its potential as a tourist attraction, an effective marketing strategy is needed. One of the most effective and efficient ways to promote this destination is through social media. This article resulting from community service will explain how social media can be used as a very effective tool to market the Mangrove Pandang Tak Jemu in Kampung Tua Bakau Serip. Choosing the right media and the right marketing strategy, social media can increase visibility thereby attracting more visitors, and ultimately support the mangrove forest environment through sustainable tourism. Optimal use of social media can help Mangrove Pandang Tak Jemu in Kampung Tua Bakau Serip become a widely known tourist destination, as well as provide education and increase awareness of the importance of the mangrove ecosystem as a lungs of the world

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)0.001
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 score0.050
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0500.006

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 head0.010
GPT teacher head0.213
Teacher spread0.204 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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Same venueJURNAL KEKER WISATASame topicCoastal Management and DevelopmentFrench-language works237,207