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Record W4402423151 · doi:10.54066/jptis.v2i3.2349

Penentuan Kelayakan Pemberian Bantuan BBM pada Nelayan menggunakan Metode Vikor

2024· article· en· W4402423151 on OpenAlexaff
Anisa Putri Pratiwi, Relita Buaton, Melda Pita Uli Sitompul

Bibliographic record

VenueJurnal Penelitian Teknologi Informasi dan Sains · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Agroindustry Studies
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsMathematicsPhysics

Abstract

fetched live from OpenAlex

Fishermen is a term for people whose daily work is catching fish or other biota that live on the bottom or surface of the water. Fishermen can also discuss and share experiences in overcoming problems in the fisheries and marine sector to meet the needs of fishermen. The government of the Fisheries and Marine Service is required to support the need for subsidized fuel for fishermen. The increase in fuel oil (BBM) has an impact on the operational costs of fishermen, because BBM is one of the main components in the daily activities of fishermen, with the high price of BBM, fishermen will face an increase in operational costs that they must spend to carry out fishing activities. This can reduce the income earned by fishermen, because higher costs will affect the profits that fishermen get from the sale of fish. So the Fisheries and Marine Service of Langkat Regency Provides Assistance for Fishermen in Langkat Regency, from the many assistance that have been distributed in this thesis I took a sample of the Fishermen of Secanggang Village. Based on the research conducted, the results obtained were that the first alternative that was a priority to receive subsidized fuel assistance for fishermen in Langkat Regency with a Q value = 0 and was entitled to be recommended. And the next priority was the second alternative with a Q value = 0.492.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
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 communication0.0010.001
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 head0.018
GPT teacher head0.225
Teacher spread0.207 · 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 designNot applicable
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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