Pengembangan Web E-Voting Menggunakan Secure Election Protocol
Bibliographic record
Abstract
Sistem e-voting akan memberikan kemudahan kepada pemilih dan panitia pelaksana dari segi waktu maupun biaya. Sistem voting melalui internet (e-voting) akan menemui permasalahan terkait keamanan komunikasi dan data sehingga diperlukan sebuah protokol kriptografi yang disebut Secure Election Protocol. Prosedur kerja dari Secure Election Protocol dengan dua panitia sentral menggunakan CTF dan CLA menjadi panitia. Protokol ini menggunakan algoritma AES-128 untuk mengamankan data yang dikirimkan, dan algoritma RSA untuk mengamankan kunci AES-128 serta menggunakan kombinasi algoritma DSA dan SHA-1 untuk membentuk tanda tangan digital dari pesan yang dikirimkan. Perangkat lunak e-voting menggunakan Secure Election Protocol dengan dua panitia sentral ini mampu mengamankan proses pemilihan online (e-voting) untuk pemilihan Ketua BITSMIKRO dengan baik dan benar. Kebutuhan teknologi e-voting yang aman di masa mendatang akan semakin besar. Penerapan kriptografi pada penelitian ini telah membuktikan perannya dalam mengamankan pemilihan online (e-voting).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".