P PENGARUH MEDIA SOSIAL, HARGA, DAN LOKASI TERHADAP KEPUTUSAN KUNJUNGAN KONSUMEN
Bibliographic record
Abstract
This scholarly inquiry endeavors to dissect the intricate dynamics through which social media—intertwined with pricing schemes and geographical accessibility—exerts influence in sculpting the cognitive and behavioral inclinations of consumers toward their decision to visit Resto Kedai Darma, situated in Klaten, Central Java. The declining number of consumer visits became the motivation for this research, which is presumed to be related to suboptimal digital promotion, perceptions of prices that do not match service quality, and the restaurant's location outside the city center. The core demographic profile identified in this study encompasses individuals aged 17 to 40 who exhibit consistent engagement with social media platforms. A total of 100 participants were selected utilizing an incidental sampling technique. Empirical data acquisition was facilitated through the dissemination of structured questionnaires, followed by analytical processing via multiple linear regression techniques, operationalized using SPSS software version 27. The empirical findings reveal that pricing exerts a statistically significant and positive influence on consumer visit decisions, while social media and location do not show significant effects. The coefficient of determination (Adjusted R²) is 11.6%, indicating that the triadic constructs of social media engagement, pricing dynamics, and spatial accessibility collectively exert measurable impacts, explaining 11.6% of the variation in consumer visit decisions. The findings suggest that price is a dominant factor influencing customer decisions, while social media and location require further strategic optimization to attract more visitors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".