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Record W4205563668 · doi:10.30871/jamn.v5i1.2892

Motion Graphic Iklan Layanan Masyarakat Edukasi Tata Tertib Rambu Lalu Lintas

2021· article· id· W4205563668 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

VenueJOURNAL OF APPLIED MULTIMEDIA AND NETWORKING · 2021
Typearticle
Languageid
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Iklan layanan masyarakat ialah iklan yang menyajikan pesan-pesan sosial yang bertujuan untuk membangkitkan kepedulian masyarakat terhadap sejumlah masalah yang harus mereka hadapi, yakni kondisi yang bisa mengancam keselarasan dan kehidupan umum. Kurangnya kesadaran oleh pengendara sepeda motor seringkali berakibat fatal terhadap dirinya dan bahkan orang lain. Bahkan banyak dari pengendara sepeda motor melanggar peraturan yang telah ditetapkan yang bertujuan untuk ketertiban berlalu lintas di jalan raya. Sehingga dibuatlah penelitian untuk melakukan produksi video motion graphic iklan layanan masyarakat mengenai edukasi tata tertib rambu lalu lintas menggunakan metode penelitian Kuantitatif dengan metode penyelesaian vaughan. Dan pada hasil analisis yang dilakukan terlihat hasil nya pada tingkat ke efektifitas yang berdasarkan interval skala likert pada ahli diperoleh predikat “Sangat Setuju” dengan nilai rata- rata 96,25% (berdasarkan rincian aspek : Grafis 90%, Tipografi 95%, animasi 100% dan audio 100%). Dan pada perhitungan EPIC Rate didapati sebesar 4.145 (berdasarkan rincian aspek : Empathy 4.19, Persuation 4.16, Impact 4.17, dan Communication 4.06 dan berdasarkan pertanyaan mengenai kinetic typografi yang sudah di masukkan pada kuisioner membuktikan bahwa penggunaan kinetic typografi efektif untuk dilakukan

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.237
Teacher spread0.219 · 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