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Record W4416689795 · doi:10.54082/jupin.1927

Model Perencanaan Tata Ruang Partisipatif untuk Pengembangan Heritage Education Tourism di Situs Cagar Budaya Kota Kapur Kabupaten Bangka

2025· article· W4416689795 on OpenAlexaff
Korri Rakasiwi, Arif Rahman, Lidiya Pratiwi, Muhammad Paisal

Bibliographic record

VenueJurnal Penelitian Inovatif · 2025
Typearticle
Language
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsGovernment (linguistics)Center (category theory)Cultural heritage

Abstract

fetched live from OpenAlex

Situs Cagar Budaya Kota Kapur di Kabupaten Bangka memiliki nilai historis tinggi sebagai pusat peradaban Sriwijaya, namun pengelolaannya masih menghadapi masalah serius seperti alih fungsi lahan, infrastruktur terbatas, dan rendahnya partisipasi masyarakat. Penelitian ini bertujuan merumuskan model perencanaan tata ruang berbasis zonasi partisipatif untuk mendukung pengembangan heritage education tourism. Metode yang digunakan adalah kualitatif deskriptif melalui observasi, wawancara, diskusi kelompok, serta telaah dokumen regulasi dan literatur. Analisis SWOT dan pendekatan spasial digunakan untuk mengidentifikasi potensi, kendala, serta penyusunan zonasi sesuai prinsip pelestarian, edukasi, dan pemberdayaan masyarakat. Hasil penelitian menunjukkan bahwa delineasi empat zona yaitu zona inti, zona penyangga, zona pengembangan, dan zona penunjang dapat meningkatkan efisiensi pengelolaan ruang. Selain itu, integrasi UMKM lokal (lidi nipah, madu kelulut/pelawan, dan kerang darah) dalam zona penunjang membuka peluang pemberdayaan ekonomi yang memperkuat partisipasi masyarakat. Kebaruan (novelty) penelitian ini terletak pada pengembangan model tata ruang partisipatif yang menggabungkan konservasi sejarah, fungsi edukatif, dan ekonomi kreatif masyarakat di kawasan cagar budaya pulau kecil. Secara teoretis, penelitian ini memperkaya literatur heritage planning dengan pendekatan spasial-edukatif-partisipatif, sedangkan secara praktis memberikan rekomendasi kebijakan untuk mewujudkan pengelolaan cagar budaya yang inklusif, adaptif, dan berkelanjutan.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.308
Teacher spread0.284 · 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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