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Record W4409802278 · doi:10.25105/jamin.v6i1.18557

PENYULUHAN PENGGUNAAN PETA DESA MENGGUNAKAN UNMANNED AERIAL VEHICLE (UAV) DI KECAMATAN CIMENYAN, KABUPATEN BANDUNG

2024· article· en· W4409802278 on OpenAlexaff
D. Raja, Fidela Rikmayanthi Kirana, Nadya Finlandini, Muhammad Rahman, Christopher Avrio Simatupang, Reinaldy Aditya

Bibliographic record

VenueJurnal Abdi Masyarakat Indonesia (JAMIN) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Agroindustry Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Creating a village map is essential for regional development planning. However, it can be costly and time-consuming. The purpose of community service is to map the area around Mandalamekar Village, Cimenyan District, Bandung Regency, as one of the supporting documents for village planning based on disaster mitigation. The scope of this community service activity includes field data acquisition, such as creating flight paths and aerial photography using UAV vehicles, as well as data processing, including ortho mosaic, digitizing maps, and spatial analysis. The community service activity will produce an Aerial Photo Image Map and Land Use Map of Mandalamekar Village, both of which will be created at a scale of 1:5000. The output from the Community Service activity can be utilized for village development planning based on disaster mitigation. Furthermore, training on drone operation and processing has been conducted with the expectation that employees of Mandala Mekar Village can utilize drone technology. The feedback from the survey suggests that the Community Service activity is aligned with the users' requirements and has the potential to offer solutions for Mandala Mekar Village.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.217
Teacher spread0.201 · 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
Published2024
Admission routes1
Has abstractyes

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