Exploring the Impact of Social Media Adoption to Small Medium Enterprises (SMEs) Performance
Bibliographic record
Abstract
An evaluation of the role of social media today reveals that it plays a vital role in current society; by January 2023, active users were at 167 million or 60. This is equivalent to four percent of the population of total Indonesia. This research invites SMEs to engage in the efficient use of social media in the management of challenges. To gather data, this research employs Google Forms to survey 130 actively involved social media users in the Jabodetabek region of Indonesia in May of 2024 with the help of the Purposive sampling technique. Using the research method employing method application software namely SMART-PLS 4 and under employing PLS-SEM, it is established that out of the five variables investigated in this study. Four out of the five hypotheses that were postulated for a corresponding test on the use of social media and as perceived for the ability of its utility, ease of use, technological impact, and compatibility yielded statistically significant outcomes.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".