Analysis of Acceptance of Karawang Responsible Service Application (Tangkar) Using Technology Acceptance Models 3 (TAM 3)
Bibliographic record
Abstract
Currently, social media plays a very important role for society. Most people even use social media such as Facebook, Instagram, Twitter, etc to convey their aspirations. Tangkar, is the name or term given to the Official Regional Complaint Portal for the Karawang Community. This application was launched on February 22, 2019. This study aims to determine the factors that can influence user intentions, in this case the people of Karawang Regency to use the Tangkar application. The research method used in this research is the Technology Acceptance Models 3 (TAM 3) method. Meanwhile, the data collection method in this study is to use a survey by distributing questionnaires to users of the Tangkar application, namely the people of Karawang Regency. The number of samples in this study were 60 respondents. This study was analyzed using the Structural Equation Model (SEM) with the help of SmartPLS 3 software. The results of this study indicate that the intention to use the Tangkar application is the main factor of respondents using the Tangkar application. The user's intention to use Tangkar application is influenced by the perceived usefulness, ease of use and subjective norms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".