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Record W7042258317

Pemetaan Potensi Objek Wisata Di Kecamatan Girisubo Kabupaten Gunungkidul Dengan Sistem Informasi Geografis

2023· dissertation· en· W7042258317 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUMS Library Center of Academic Activities (Universitas Surakarta) · 2023
Typedissertation
Languageen
FieldMaterials Science
TopicRadiation Shielding Materials Analysis
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsTourismTourist attractionGeographic information systemDistribution (mathematics)GeoreferenceField surveySpatial analysis
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT
\nGirisubo sub-district is a sub-district directly adjacent to the south coast of Java which holds a lot of tourism potential, but the high potential is still a lot of attractions that have not been developed which amounted to 26 attractions compared to the number of attractions that have been developed, so a study was made entitled "Mapping the Potential of Tourism Objects in Girisubo District, Gunungkidul Regency with the Help of Geographic Information Systems", with the aim of 1) mapping the distribution of potential tourist attractions in Girisubo District, 2) analyzing the level of potential of marine and natural attractions in Girisubo District, and 3) analyzing the factors causing the unmanaged tourist attractions in Girisubo District. The methods used in this research are secondary data analysis method and survey method supported by field observation. Field observations were conducted to support secondary data and aimed to determine the physical condition of the tourist attraction and obtain the coordinate location. While the data analysis method uses scoring and classification analysis methods. The results showed that: 1) tourism objects that have not been developed in Girisubo sub-district are scattered in 4 villages namely Jepitu, Balong, Pucung, and Songbanyu villages, 2) the potential level of tourism objects in Girisubo sub-district is divided into low and medium level classifications, The tourist attractions with low-level classification include Watubonang Beach, Ngusalan Beach, Nglegundi Beach, Brumbun Beach, Mount Minjung, Jepitu Community Forest, Pulejajar Cave River, Mbubuk Beach, Embung Bandung, Embung Dungbendo, Embung Mbendo, Embung Jirak, Embung Tambur, Margatindak Cave, and Manggir Cave. While tourist attractions with a moderate level classification are Pesewan Beach, Dander Beach, Wedanan Beach, Grendan Beach, Ngrengisan Beach, Botorubuh Beach, Watukebo Beach, Sinden Beach, Ngungap Beach, Tanjungmenyer Beach, and Watubolong Beach. 3) As for the factors that have not managed the tourist attraction in Girisubo Sub-district are caused by inadequate human resources, lack of pokdarwis training, cost constraints, minimal accessibility, lack of accommodation, attractions and cooperation with various parties.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.007
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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