Memanfaatkan COBIT 5 untuk Meningkatkan Keamanan Sistem Informasi pada Lembaga Pendidikan (Studi Kasus : Universitan Z)
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.
Bibliographic record
Abstract
Kebutuhan akan sistem informasi yang aman dan terpercaya menjadi salah satu aspek yang vital bagi lembaga pendidikan di era digital saat ini. Sistem informasi yang handal mampu meningkatkan efisiensi operasional serta kualitas pelayanan dan keamanan data, yang semuanya sangat penting bagi institusi pendidikan seperti Universitas Z. Metodologi yang digunakan penulis dalam pelaksanaan tugas akhir ini adalah metodologi COBIT 5 yang berfokus pada proses APO13 dan DSS05. Penelitian ini akan membahas mengenai memanfaatkan COBIT 5 untuk meningkatkan keamanan sistem informasi di Universitas Z, dengan harapan dapat memberikan kontribusi nyata dalam meningkatkan keamanan data dan sistem di lembaga pendidikan lainnya. Sehingga Penerapan COBIT 5 di Universitas Z telah menghasilkan manajemen risiko yang sistematis dan komprehensif. Kata Kunci : COBIT 5, keamanan sistem informasi, proses APO13, DSS05
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it