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Record W2736816756 · doi:10.31328/jointecs.v2i1.411

Sistem Pengambil Keputusan untuk Menentukan Kelayakan Penerima Kredit Mobil di PT. Adira Finance Cabang Kota Pasuruan

2017· article· en· W2736816756 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

VenueJOINTECS (Journal of Information Technology and Computer Science) · 2017
Typearticle
Languageen
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsDocumentationBusinessFinanceProcess (computing)SoftwareAccountingComputer scienceOperating system

Abstract

fetched live from OpenAlex

PT. Adira Finance branch at Pasuruan city is one of enterprise that budged in funding sector and vehicle insurance. Advisability policy give credit a car for customer still use conventional method and need a lot of time to give advisability policy give credit to customer. The purpose of this study is to built a software as device to help make decision for the leader in giving credit to customer and to make easier the customer in delivery information about submission their credit. The methodology of this research is field research , interview and library research. Determination of the feasibility of using five credit recipient C. Decision Support System credit aplication can make easier in take a decision to determine advisability a customer in accept credit. It can take in hand a process for renewal customer data, the data of car, and the reporting process so. It have documentation about a good software.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.007
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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