AUDIT SISTEM INFORMASI DALAM MENGUKUR KEPATUHAN ISO 27002
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengevaluasi tingkat kepatuhan PT Jaya Sawit Langkat (PT JSL) terhadap standar ISO 27002 dalam konteks keamanan informasi. pada era digital saat ini, perusahaan menghadapi ancaman serius terhadap kerahasiaan, integritas, serta ketersediaan data. Meskipun pentingnya keamanan informasi diakui, banyak perusahaan, termasuk PT JSL, sering kali mengabaikan implementasinya.Metode penelitian yang dipergunakan meliputi studi literatur, observasi, dan wawancara menggunakan pegawai untuk memahami praktik keamanan yang ada dan tantangan yang dihadapi. hasil audit menunjukkan bahwa tingkat kematangan implementasi kontrol keamanan informasi di PT JSL berada pada kategori menengah dengan nilai rata-rata 2.49. Hal ini mengindikasikan bahwa meskipun perusahaan telah memulai penerapan kontrol sesuai ISO 27002, masih ada banyak area yang memerlukan perbaikan. Rekomendasi utama mencakup peningkatan pelatihan bagi karyawan tentang keamanan informasi dan pelaksanaan audit berkala untuk mengidentifikasi dan memperbaiki kelemahan pada sistem keamanan yang ada. dengan langkah-langkah tersebut, diharapkan PT JSL dapat menaikkan keamanan data dan kepercayaan pelanggan.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.013 |
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".