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Record W4391241070 · doi:10.32734/jba.v1i2.11217

PENGARUH PERSEPSI KEMUDAHAN DAN PERSEPSI KEAMANAN TERHADAP MINAT PENGGUNAAN E-MONEY DI KALANGAN GENERASI MILLENIAL

2022· article· en· W4391241070 on OpenAlexaff
Adinda, Ainun Mardhiyah

Bibliographic record

VenueJournal Business Administration Entrepreneurship and Creative Industry · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Technological advances in payment systems are slowly shifting the role of cash as a means of payment to more efficient and economical forms of non-cash payments. Therefore, the development of the use of non-cash payment instruments needs serious attention. This study aims to determine how the Effect of Perceptions of Ease and Perceptions of Security on Interest in Using E-money. This study uses quantitative research methods with an associative approach. The population in this study were e-money users in the Medan Baru District area. The results showed that the Ease of Perception had a positive and significant effect of 27.1% on Interest in Using E-money and Perception of Security had a positive and significant effect of 40% on Interest in Using. Based on calculations with the coefficient of determination, the R value is 81.9%, which indicates that the relationship between perceived convenience and perceived security on interest in using e-money is quite close. The Rsquare value of 0.671 indicates that 67.1% of the Usage Interest variable can be explained by the Ease of Perception and Perception of Security. While the rest is influenced by other variables not examined in this study.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.291
Teacher spread0.258 · 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; a candidate call from one teacher head, not a consensus.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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