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STUDI KERUANGAN DAN KELEMBAGAAN PENGELOLAAN EKOWISATA MANGROVE DI NEGERI AMAHAI, KABUPATEN MALUKU TENGAH

2025· article· en· W4414736399 on OpenAlexaff
Yosep M Reyaan, James Abrahamsz, Erawan Asikin

Bibliographic record

VenueTRITON Jurnal Manajemen Sumberdaya Perairan · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Agroindustry Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsEcotourismMangroveNonprobability samplingSWOT analysisTourism

Abstract

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Ecotourism is a tourist activity that aims to conserve. In its implementation, institutions have a very important role for sustainable ecotourism management. This study aims to determine the forms of space utilization in mangrove ecotourism, analyze the suitability and carrying capacity of ecotourism areas, analyze the role of institutions in influencing the success of ecotourism management, and formulate a strategy for managing ecotourism in Negeri Amahai. The research was conducted in Negeri Amahai, Central Maluku Regency in January-May 2023. Mangrove data were collected by purposive sampling using transect lines. Analysis of land suitability and carrying capacity using established formulas. Management strategies using SWOT and TOWS with policy priorities further analyzed with AHP. The results showed, the tourist space in mangrove ecotourism is in the form of reception space, service space and tourist space. There are various forms of utilization in the space both supporting ecotourism activities such as educational facilities, trade, trash bins, sanitation and communication, and there are still activities that threaten such as mangrove logging and sand mining. The suitability of mangrove ecotourism at station I is categorized as “Very Suitable” with IKW 85%, while at station II as “Suitable” with IKW 64%. The carrying capacity of mangrove ecotourism area can accommodate 31 tourists/day. The role of institutions in the management of mangrove ecotourism is considered “Not Optimal” because it does not yet have institutions or rules that focus on management of mangrove ecotourism. There are 11 strategies and 5 priorities in managing mangrove ecotourism in Negeri Amahai. ABSTRAK Ekowisata merupakan suatu kegiatan wisata yang bertujuan untuk konservasi. Dalam pelaksanaanya, kelembagaan memiliki peran yang sangat penting untuk pengelolaan ekowisata berkelanjutan. Penelitian ini bertujuan untuk mengetahui bentuk-bentuk pemanfaatan ruang pada ekowisata mangrove, menganalisis kesesuaian dan daya dukung kawasan ekowisata, menganalisis peran kelembagaan dalam mempengaruhi keberhasilan pengelolaan ekowisata, dan memformulasikan strategi pengelolaan ekowisata Negeri Amahai. Penelitian dilakukan di Negeri Amahai, Kabupaten Maluku Tengah pada Januari-Mei 2023. Pengambilan data mangrove secara purposive sampling dengan menggunakan garis transek. Analisis kesesuaian lahan dan daya dukung menggunakan rumus yang ditetapkan. Strategi pengelolaan menggunakan SWOT dan TOWS dengan prioritas kebijakan dianalisis lebih lanjut dengan AHP. Hasil penelitian menunjukan bahwa ruang wisata pada ekowisata mangrove berupa ruang penerimaan, ruang pelayanan dan ruang wisata. Terdapat beragam bentuk pemanfaatan pada ruang tersebut baik yang mendukung kegiatan ekowisata seperti fasilitas edukasi, perdagangan, tempat sampah, sanitasi dan komunikasi, serta aktivitas yang mengancam seperti penebangan mangrove dan penambangan pasir. Kesesuaian ekowisata mangrove pada stasiun I dikategorikan “Sangat Sesuai” dengan IKW 85%, sedangkan pada stasiun II dikategorikan “Sesuai” dengan IKW 64%. Daya dukung kawasan ekowisata mangrove Negeri Amahai mampu menampung 31 wisatawan/hari. Peran kelembagaan dalam pengelolaan ekowisata mangrove Negeri Amahai dinilai “Belum Optimal” dikarenakan belum memiliki lembaga maupun aturan yang fokus pada pengelolaan ekowisata mangrove. Terdapat 11 strategi dan 5 prioritas dalam pengelolaan ekowisata mangrove Negeri Amahai. Kata Kunci: Ekowisata, mangrove, kesesuaian, daya dukung, kelembagaan

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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