PENGARUH KEPERCAYAAN MEREK TERHADAP LOYALITAS KONSUMEN PADA PENGGUNA AIR MINUM KEMASAN ARINDO KOTA KENDARI
Bibliographic record
Abstract
Pengaruh Kepercayaan Merek Terhadap Loyalitas Konsumen Pada Pengguna Air Minum Kemasan Arindo PT. Aromaqua Segarindo Kota Kendari (Studi Kasus Pada Kecamatan Baruga Kota Kendari). Penelitian ini bertujuan untuk menganalisis pengarub kepercayaan merek terhadap loyalitas konsumen pada pengguna air minum kemsan Arindo PT. Aromaqua Segarindo Kota Kendari. Kepercayaan merek dalam penelitian ini dikonsepsikan sebaagai variable laten yang pengukurannya didasarkaan pada dua (2) dimensi brand trust (kepercayaan merek) menurut Kotler, yang diuji melalui variabel reliability (keterandalan merek) dan variabel intentionality (minat dan niat untuk membeli). Loyalitas konsumen dikonsepsikan sebagai variabel observasi. Responden penelitian sebanyak 50 orang, ditentukan secara sengaja. Pengumpulan data dilakukan dengan menggunakan angket. Setiap jawaban item pertanyaan diukur dengan menggunakan skala Likert. Hasil uji hipotesis dengan tingkat α = 0,05, menunjuikan bahwa nilai Fsig (0.000) lebih kecil dari α 0,05, sehingga dinyatakan bahwa variabel kkepercayaan merek yang meliputi reliability (X1), intentionality (X2) secara simultan berpengaruh signifika terhadap loylitas konsumen (Y) pada taraf kepercayaan 95%. Secara parsial, hasil pengujian juga menunjukan bahwa variabel reliability (X1) dan intentionality (X2) berpengaruh signifikan terhadap loyalitas konsumen.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".