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Record W4415360009 · doi:10.59934/jaiea.v5i1.1554

Digital Signage Application System at STMIK Kaputama

2025· article· W4415360009 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 Artificial Intelligence and Engineering Applications (JAIEA) · 2025
Typearticle
Language
FieldEngineering
TopicIndustrial Automation and Control Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsDigital signageWaterfall modelSignageAndroid (operating system)Systems development life cycleInformation systemProcess (computing)Class (philosophy)

Abstract

fetched live from OpenAlex

This research focuses on the development of a Digital Signage Application System as a modern solution for delivering academic information at STMIK Kaputama. The inputs of this research include announcement data, class schedules, guidance schedules, activity photos, and campus profiles. The process is carried out through stages of needs analysis, system design using the System Development Life Cycle (SDLC) waterfall model, web-based implementation using the CodeIgniter PHP framework and MySQL database, and integration with Android Set Top Box (STB) devices as display media to LED monitors. The output produced is a Digital Signage system capable of displaying campus information dynamically, in real-time, and easily managed through an admin interface.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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