Audit Sistem Informasi Penjualan Pada Toko Halim Maju Menggunakan Framework COBIT 5
Bibliographic record
Abstract
Penelitian ini mengevaluasi sistem informasi penjualan di Toko Elektronik Halim Maju, yang memiliki 10 karyawan. Sistem informasi tersebut digunakan untuk mencatat transaksi dan mengelola inventaris. Namun, terdapat kelemahan dalam pengelolaan risiko operasional, konsistensi pelaksanaan, dan efisiensi sistem, yang dapat memengaruhi kinerja toko. Audit dilakukan menggunakan framework COBIT 5, khususnya pada domain Deliver, Service, and Support (DSS), untuk menilai kapabilitas sistem informasi. Audit ini penting karena tingginya volume transaksi bulanan yang berpotensi menimbulkan masalah, seperti ketidaktepatan data atau keamanan informasi jika tidak dikelola dengan baik. Hasil audit menunjukkan bahwa sistem informasi toko berada pada Level 2 (Established). Hal ini menunjukkan sistem telah memiliki proses yang terdefinisi tetapi belum sepenuhnya konsisten. Untuk meningkatkan kinerja, diperlukan upaya perbaikan agar dapat mencapai Level 3 (Predictable), di mana proses menjadi lebih terorganisir dan terkendali.
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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".