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Record W4293015626 · doi:10.55601/jsm.v17i2.385

Replikasi TAM pada Penggunaan Portal Akademik

2016· article· id· W4293015626 on OpenAlexaff
Erwin Setiawan Panjaitan, Fitri Aryanti

Bibliographic record

VenueJurnal SIFO Mikroskil · 2016
Typearticle
Languageid
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Penelitian ini dilakukan dengan mengadopsi Technology Acceptance Model yang??? dikemukakan oleh Fred D. Davis (1989) dengan mengambil beberapa variabel yang diperlukan. Tujuan dari penelitian ini adalah untuk menguji persepsi manfaat dan persepsi kemudahan??? terhadap minat perilaku menggunakan portal akademik. Sampel yang digunakan dalam penelitian ini adalah mahasiswa/I fakultas MIPA USU yang menjadi pengguna akhir dari sistem ini. Teknik pengambilan sampel yang digunakan adalah non-probability sampling menggunakan metode quota sampling. Jumlah sampel dalam penelitian ini sebanyak 70 responden. Penelitian ini menggunakan metode penelitian kuantitatif dan teknik analisis data yang digunakan yaitu regresi liniear berganda. Pengujian hipotesis pada penelitian ini dilakukan dengan menguji pengaruh persepsi manfaat dan persepsi kemudahan terhadap minat perilaku menggunakan portal akademik melalui pengujian secara simultan (Uji-F) dan pengujian secara parsial (Uji-t). Hasil penelitian secara simultan membuktikan bahwa persepsi manfaat dan persepsi kemudahan secara bersama-sama berpengaruh positif dan signifikan terhadap minat perilaku. Secara Parsial, persepsi manfaat berpengaruh positif dan signifikan terhadap minat perilaku dan persepsi kemudahan juga berpengaruh positif dan signifikan terhadap minat perilaku.

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.

How this classification was reachedexpand

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.012

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 head0.058
GPT teacher head0.346
Teacher spread0.289 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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