The role of quality and trust on using website news
Bibliographic record
Abstract
This study is to analyze the influence of the quality of information on the decision to choose CNNIndonesia.com media either directly or through the mediation of trust variables. The tremendous growth of cyber media in Indonesia, followed by the development of online media, has made people more careful in choosing online media. Meanwhile, the use and gratification theory states that the most important role of media is to meet people's needs and motivations, how certain media are sought and selected to meet their needs. This study uses a survey method through a quantitative approach positivistic. The sample was determined by an accidental sampling technique with a sample of 115 respondents. Data analysis was performed using Partial Least Square analysis with the SmartPLS version 3 program. The data analysis shows that the quality of information has a significant effect on increasing trust in CNNIndonesia.com media, the quality of information has a significant effect in increasing the decision to choose CNNIndonesia.com media, and trust has a significant effect in increasing the decision to choose CNNIndonesia.com media. This study also found that the trust variable was able to mediate the effect of information quality on the decision to choose CNNIndonesia.com media.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".