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Record W3130423789 · doi:10.31479/jnk.v3i2.159

Pertanggung Jawaban Hukum Atas Terjadinya Wanprestasi Dalam Penerapan Perjanjian Sewa Pesawat

2018· article· id· W3130423789 on OpenAlexaboutno aff
Martha Emylia Taurisia, Fauzie Yusuf Hasibuan, Ahmad Muliadi

Bibliographic record

VenueJurnal Nuansa Kenotariatan · 2018
Typearticle
Languageid
FieldSocial Sciences
TopicLegal and Policy Analysis in Indonesia
Canadian institutionsnot available
Fundersnot available
KeywordsLeaseLawSupporterNormativeAeronauticsBusinessEngineeringPolitical scienceHistory

Abstract

fetched live from OpenAlex

The practice of aircraft lessor company with aircraft lessee company may allow “default” because one party does not fulfill its obligations properly and correctly in accordance with the contents of the aircraft lease agreement the. The method used in this research is normative juridical research supported by empirical juridical research. The data used are secondary data composed of primary law, secondary law materials and materials law tertier. In addition the primary data is also used as the supporter of the legal materials of secondary data. For the data analysis was done with a qualitative analysis of the juridical method. The results showed that PT. Air Born Indonesia’s responsibility to lease aircraft in aircraft lease agreement lease agreement air transportation can be categorized as a reciprocal or bilateral agreement. In this case PT Air Born Indonesia as the holder does not fulfill the obligations as agreed in the agreement for not paying the De Havilland Canada DHC-6/300 Twin Otter MSN 518 PK-BAF registration fee corresponding to the amount rent with a specified time, changing the aircraft without the knowledge of Unity Group Ltd, operating the aircraft not in accordance with the agreement, then it is said to have made a default.

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)0.002
metaresearch head score (Gemma)0.000
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0050.002
Scholarly communication0.0010.002
Open science0.0030.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.022
GPT teacher head0.305
Teacher spread0.283 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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