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Analisis Audit Sistem Informasi Pada Pengaruh Pelayanan Nasabah di BPJS Ketenagakerjaan

2024· article· en· W4404493130 on OpenAlexaff
Ikhsan Arif, Prisa Abela, Nurul Syahrani, Dina Ervianna Simarmata

Bibliographic record

VenueJurnal Sistem Informasi dan Ilmu Komputer · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsBusinessBusiness administrationAuditAccounting

Abstract

fetched live from OpenAlex

Information system audits have an important role in ensuring the quality of customer service at BPJS Ketenagakerjaan. This study aims to analyze the effect of information system audits on customer service at BPJS Ketenagakerjaan, with a case study focus on the Binjai branch office. The background of this research is the important role of information systems in supporting BPJS Ketenagakerjaan operations and services. Along with technological developments, the reliability, security and efficiency of information systems are crucial in maintaining the quality of service to customers. Therefore, an information system audit is needed to ensure that the system runs according to predetermined standards and is able to provide the best service.

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), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0040.007
Open science0.0010.001
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 head0.011
GPT teacher head0.211
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 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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