Penerapan Algoritma Linier Congruent Method Pada Pengacakan Soal Ujian Berbasis Online di SD Muhammadiyah Sei Cabang
Why this work is in the frame
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Bibliographic record
Abstract
This study was conducted at SD Muhammadiyah Sei Cabang, a private school in Langkat Regency, which still uses manual examination methods with identical questions for all students. This method is considered ineffective because it allows students to cheat, leading to exam results that do not accurately reflect their abilities. To address this issue, the study developed a web-based examination system using the Linear Congruent Method (LCM) to generate randomized question numbers. With LCM, each student receives a different set of question numbers, making the exam process more effective and fair. The system was built using PHP programming language and MySQL database, enabling efficient data storage and processing. The implementation of this system resulted in improved accuracy in assessment and reduced cheating potential during exams at the school.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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