Audit Sistem Informasi Absensi Menggunakan Cobit 5 (Studi Kasus ; PT. PLN Persero Binjai)
Bibliographic record
Abstract
The development of information systems is now widely used in the business world, both in the living environment and even in the work environment, such as the use of the attendance information system at PT PLN PERSERO. Attendance in an agency is an important factor in human resource management. Accurate and objective information regarding an employee's attendance can present the quality and productivity of performance, determine the size of performance allowances and the general level of employee discipline in the agency. The process of recording and reporting employee absences is a repetitive process that is used at certain times such as entry time, departure time and holidays. It is recommended that audits of this system be carried out periodically or annually, so that the expected level of maturity can be achieved, and as a whole, not just the attendance information system, so that all aspects of work operations can also be evaluated so as to improve employee performance in general. From the results of the maturity level assessment, several findings were obtained in each domain studied, namely with the EDM03 domain having a value of 3.00, it was found that information and data security problems needed to be improved, with the EMD05 domain having a value of 2.93, problems were found that there were no written regulations that could be used as a reference, with domain AP015 with a value of 3.13 found a problem that there was still a difference between cost allocation and actual costs with domain 1P012 with a value of 3.07, a problem was found that there were no risk response regulations available, with domain DSS02 with a value of 3.13 there were no written regulations that could be used as a reference.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 0.042 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".