Analisis Audit Sistem Informasi Absensi Di PT. Clay Jaya Bersama Dengan Framework COBIT-5 Dengan Domain MEA
Bibliographic record
Abstract
Pada era globalisasi, teknologi informasi (TI) memainkan peran penting dalam efisiensi operasional perusahaan, salah satunya melalui sistem absensi berbasis fingerprint. Penelitian ini bertujuan untuk mengevaluasi efektivitas sistem tersebut di PT. CLAY JAYA BERSAMA menggunakan kerangka kerja COBIT-5 pada domain MEA (Monitoring, Evaluate, and Assess). Metode yang digunakan meliputi observasi, studi literatur, wawancara, kuesioner, dan dokumentasi. Hasil penelitian menunjukkan tingkat kapabilitas sistem berada pada level Established Process dengan rata-rata nilai 2,94 dari skala 1–4. Hal ini mencerminkan bahwa sistem telah terdokumentasi dengan baik, memiliki pengelolaan yang terstruktur, dan mampu memenuhi kebutuhan operasional perusahaan. Kesimpulan ini mengindikasikan bahwa implementasi teknologi informasi di PT. CLAY JAYA BERSAMA berjalan efektif dan mendukung tujuan bisnis yang diharapkan.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
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".