Analisis Efektivitas Pelaksanaan Bauran Promosi Pada Hotel The Lombok Lodge Dengan Menggunakan Metode Epic Model
Bibliographic record
Abstract
Dalam pelaksanaan promosi hotel The Lombok Lodge, hotel tersebut menerapkan promosi melalui periklanan, promosi penjualan, penjualan pribadi dan pemasaran langsung, dimana periklanan dilakukan melalui katalog, promosi penjualan dilakukan melalui pemberian potongan harga sewa, penjualan pribadi dilakukan melalui agen marketing dan pemasaran langsung dilakukan melalui customer service. Terdapat beberapa metode yang dapat digunakan untuk menganalisis efektivitas bauran promosi berdasarkan dampak komunikasi yang ditimbulkan, yaitu: MMP (Media Mix Planing), CRI (Costomer response index), DRM (Direct rating method) dan EPIC Model.EPIC Model yang digunakan untuk mengukur efektivitas bauran promosi yang mencakup empat dimensi kritis, yaitu: empati (empathy), persuasi (persuasion), dampak (dampak) dan komunikasi (communication).Pada penelitian ini jenis data yang digunakan adalah data kualitatif yang dikuantitatifkan.Jenis penelitian yang digunakan adalah penelitian deskriptif eksploratif.Secara keseluruhan pelaksanaan bauran promosi pada hotel The Lombok Lodge telah efektif, terbukti dari hasil analisis EPIC Model secara keseluruhan sebesar 4.01, nilai tersebut masuk dalam rentang skala penilaian 3.41 – 4.20 (Efektif).
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".