Sistem Informasi Monitoring Data Obat di Puskesmas Bontoperak Kabupaten Pangkajene dan kepulauan
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 design and create applications that can monitor drug data, namely incoming drug data, outgoing drugs, drug stocks and report making. The research method used is R&D because researchers want to produce products and test the effectiveness of the products in order to function. While the pngujian method on this system uses black box testing which aims to perform tests based on system details such as the appearance, functions and suitability of the function flow of the system. From the results of system testing, all functions in the system can function properly so as to help the performance of the officers in the health center, especially those who handle drug data. The drug data monitoring information system has been successfully designed to be used by the Head of Puskesmas, warehouse officers, and pharmacy officers. Drug warehouse officers are given the facility to enter data on sources of funds, suppliers, drugs and conduct drug transactions in and out of the warehouse. Furthermore, pharmacy officers can enter patient data and make drug transactions out at the pharmacy. As for the Head of puskesmas has facilities to be able to see the report and then print it.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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