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Record W4391938384 · doi:10.59697/jtik.v6i2.216

IMPLEMENTASI ALGORITMA OTP DAN STEGANOGRAFI EOF DALAM PENYISIPAN PESAN TEKS PADA CITRA

2022· article· id· W4391938384 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJTIK (Jurnal Teknik Informatika Kaputama) · 2022
Typearticle
Languageid
FieldComputer Science
TopicComputer Science and Engineering
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsArtComputer science

Abstract

fetched live from OpenAlex


 Penggunaan informasi media citra mempunyai beberapa kelemahan, salah satunya adalah mudahnya dimanipulasi oleh pihak-pihak tertentu dengan bantuan teknologi yang berkembang sekarang ini. Upaya yang dapat dilakukan dalam peningkatan pengamanan pengiriman informasi citra adalah kriptografi, yaitu ilmu dan seni untuk menjaga keamanan pesan. Pada penelitian ini diterapkan metode One Time Pad dan Stegnografi End Of File yang bertujuan untuk memperoleh cipher yang lebih kuat dengan menyisipkan pesan kedalam citra sehingga susah untuk di sadap. Algoritma One Time Pad untuk mengenkripsi dan dekripsi, Stegnografi End Of File yang digunakan untuk mengencoding dan mendecoding citra. Hasil dari penelitian ini menunjukkan bahwa dengan menerapkan algoritma One Time Pad dan Stegnografi End Of File dapat mengamankan pesan yang disisipkan kedalam citra dan mengamankan kunci untuk kebutuhan data. Waktu proses encoding dan decoding di pengaruhi oleh banyaknya pesan yang akan dirahasiakan.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0030.000
Scholarly communication0.0030.006
Open science0.0070.006
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.016
GPT teacher head0.238
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it