Pengaruh Kualitas Produk, Persepsi Harga dan Word Of Mouth Terhadap Keputusan Pembelian di Canada Fried Chicken Pasar Minggu
Bibliographic record
Abstract
Tujuan dari penelitian ini adalah untuk menganalisa bagaimana kualitas produk, persepsi harga dan word of mouth terhadapa keputusan pembelian pada Canada Fried Chicken Pasar Minggu dengan metode kuantitatif. Penelitian ini menggunakan data primer, data yang diperoleh dengan cara menyebarkan kuisioner secara acak kepada 100 konsumen di Canada Fried Chicken Pasar Minggu dengan teknik incidential sampling. Penelitian ini menggunakan metode analisis regresi linear berganda yang meliputi uji validitas dan reliabilitas, uji asumsi klasik, analisis regresi berganda, analisis koefisien determinasi (R2), serta pengujian hipotesis dengan uji t dan uji F dengan bantuan perangkat lunak spss 26. Hasil dari penelitian menunjukan bahwa variabel kualitas produk memiliki pengaruh positif dan signifikan secara persial terhadap keputusan pembelian, lalu persepsi harga berpengaruh positif dan signifikan secara persial terhadap keputusan pembelian, selanjutnya word of mouth berpengaruh positif dan signifikan secara persial terhadap keputusan pembelian. Secara simultan menunjukan kualitas produk ,persepsi harga, ,word of mouth berpengaruh signifikan terhadap keputusan pembelian di Canada Fried Chicken Pasar Minggu. Pada hasil dari penelitian ini menunjukan bahwa Canada Fried Chicken Pasar Minggu perlu memepertahankan kualitas produknya secara efektif dan efisien, agar keputusan pembelian di Canada Fried Chicken Pasar Minggu meningkat penjualannya
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".