PENERAPAN SISTEM INFORMASI MANAJEMEN ANALISIS KELEMBAGAAN KABUPATEN CIANJUR DALAM MENINGKATKAN KINERJA BKPSDM KABUPATEN CIANJUR
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
This research aims to analyze the application of the Cianjur Regency Institutional Analysis Management Information System (Sianjab Manjur) in improving the performance of the Cianjur Regency BKPSDM, with a focus on the implementation of Sianjab Manjur as well as the supporting factors and obstacles faced and the efforts made by the Cianjur Regency BKPSDM in overcoming obstacles. the. The research methods used include interviews, secondary data collection, and data analysis. The research results show that although Sianjab Manjur has had a positive impact in improving the performance of BKPSDM Cianjur Regency, there are several challenges that need to be faced in its implementation. The first challenge is related to data security. As an information system that stores sensitive data regarding personnel, Sianjab Manjur must be able to maintain data security properly so that it is not misused by unauthorized parties. The second challenge is related to employee acceptance and adaptation to new information systems. Using Sianjab Manjur requires acceptance and adaptation from employees, especially those who are used to manual systems. BKPSDM needs to increase outreach and training efforts to employees so that they can master and use Sianjab Manjur well.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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