Sistem Informasi Berbasis Web Untuk Pelaporan Kriminalitas Dan Monitoring Kinerja Pada Seluruh Polsek Di Wilayah Kabupaten Madiun
Bibliographic record
Abstract
In the Madiun, the recording process (incident reporting) carried out by members of the Sector Police still uses printed type and is sent in the form of an official letter. In the police supervision section, the police in this area are still manual, namely recapitulating and printing activities to be reported to the police chief. The purpose of this research is to create a website-based information system that will feature the process of reporting criminal & non-criminal events as well as performance features for police officers who function as supervision and monitoring of police performance. The development method used in this research is a waterfall with the stages of gathering requirements, the design process, implementation, integration or testing and the last is operation. In testing the system, the author uses the Blackbox Testing method in which the functionality of this system will be tested whether it is as expected or not. Based on these tests the authors can draw the conclusion that with this system it can make it easier for police members in the process of reporting criminal and non-criminal events around them and make it easier for the police chief in the process of monitoring or monitoring the performance of his members.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".