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Record W4404337320 · doi:10.61132/saturnus.v2i3.171

Audit Sistem Informasi Absensi Karyawan Berbasis Cobit 4.1

2024· article· en· W4404337320 on OpenAlex
Nadila Ayudiapasa, Pujiani Pujiani, Ratna Cantika

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

VenueSaturnus · 2024
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsCOBITAuditComputer scienceBusinessOperating systemInformation technologyAccounting

Abstract

fetched live from OpenAlex

Employee attendance information systems are an important component in human resource (HR) management in various organizations. Auditing attendance system information is necessary to ensure that the system runs effectively and efficiently, and complies with applicable regulations and policies. COBIT 4.1 (Control Objectives for Information and Associated Technologies) is an audit framework that can be used to deploy attendance information systems. This research aims to conduct an audit of the employee attendance information system using the COBIT 4 framework. This audit was carried out to evaluate the effectiveness of internal control, compliance with regulations, and operational efficiency of the employee attendance information system at XYZ company. The research method used is a combination of qualitative and quantitative, including interviews, observation and testing. The research results show that in general the employee attendance information system has been running well, but there are still several findings related to control and compliance weaknesses that need to be improved. The recommendations provided include improving access rights management, monitoring activities, as well as improving procedures and documentation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.232
Teacher spread0.226 · 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