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Satisfaction Level of the Academic Community with the Implementation of WEB-Based SIAKAD IAKN Tarutung (Comparison: Implementation of SIAKAD UIN-Sumatera Utara)

2023· preprint· en· W4388573238 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

VenuePreprints.org · 2023
Typepreprint
Languageen
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsTaylor College and Seminary
Fundersnot available
KeywordsAcademic communitySERVQUALWork (physics)Higher educationMedical educationValue (mathematics)PsychologyComputer scienceKnowledge managementBusinessService (business)EngineeringMarketingService qualityPolitical scienceLibrary scienceMedicine

Abstract

fetched live from OpenAlex

SIAKAD is a system developed to meet the needs of the academic community as a whole. Implementation of SIAKAD is based on three satisfaction indicators: access speed, ease of access and timeliness. Qualitative and quantitative methods on SERVQUAL analysis. Then analysed with statistical data as a comparison of satisfaction implementation in each academic community in IAKN and UIN universities. This study shows that the purpose of satisfaction affects the value of the academic community in providing an excellent and destructive impact on the value of work in higher education as well as the involvement of various elements in higher education to determine how the academic information system (SIAKAD) should be built to meet the expectations of its users and following SIAKAD standards in general in higher education.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.002
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 head0.246
GPT teacher head0.430
Teacher spread0.184 · 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