PENGARUH BEAUTY INFLUENCER, ELECTRONIC WORD OF MOUTHDAN BRAND IMAGE TERHADAP NIAT BELI PRODUK SKINTIFIC DIBANDAR LAMPUNG
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui pengaruh Beauty Influencer, Electronic Word of Mouth, dan Brand Image terhadap Niat Beli produk Skintific di Bandar Lampung. Skintific merupakan brand skincare asal Kanada yang mulai populer di Indonesia, terutama di kalangan generasi muda, melalui strategi pemasaran digital berbasis media sosial. Promosi yang dilakukan melalui influencer ternama, ulasan daring dari pengguna, serta citra merek yang kuat menjadi bagian penting dalam membentuk dalam niat beli konsumen. Penelitian ini menggunakan metode kuantitatif dengan pendekatan deskriptif. Populasi dalam penelitian ini adalah masyarakat di Kota Bandar Lampung yang mengetahui dan memiliki niat membeli produk Skintific. Teknik pengambilan sampel dilakukan secara purposive sampling, dengan jumlah responden sebanyak 126 orang. Data dikumpulkan melalui kuesioner menggunakan skala Likert, dan dianalisis menggunakan regresi linier berganda dengan bantuan program SPSS. Hasil penelitian menunjukkan bahwa, variabel Beauty Influencer, Electronic Word of Mouth, dan Brand Image berpengaruh positif dan signifikan terhadap Niat Beli produk Skintific. Variabel Electronic Word Of Mouth menjadi variabel yang paling dominan memengaruhi niat beli.Temuan ini menunjukkan bahwa strategi pemasaran berbasis digital yang melibatkan influencer terpercaya, ulasan online yang positif, serta pencitraan merek yang kuat, sangat efektif dalam mendorong niat beli konsumen, khususnya di kalangan generasi muda di Kota Bandar Lampung. Kata Kunci : Beauty Influencer, Electronic Word Of Mouth, Brand Image, Niat Beli, Skintific This research aims to find out the influence of Beauty Influencer, Electronic Word of Mouth, and Brand Image on the Intention to Buy Skintific products in Bandar Lampung. Skintific is a skincare brand from Canada that is becoming popular in Indonesia, especially among the younger generation, through a social media-based digital marketing strategy. Promotions carried out through well- known influencers, online reviews from users, and a strong brand image are an important part of shaping consumer buying intentions. This research uses a quantitative method with a descriptive approach. The population in this study is people in Bandar Lampung City who know and have the intention to buy Skintific products. The sampling technique was carried out by purposive sampling, with a total of 126 respondents. Data is collected through questionnaires using the Likert scale, and analyzed using multiple linear regression with the help of the SPSS program. Research results show that, the variables of Beauty Influencer, Electronic Word of Mouth, and Brand Image have a positive and significant effect on the Purchase Intention of Skintific products. The Electronic Word Of Mouth variable is the most dominant variable that affects buying intentions. This finding shows that digital- based marketing strategies involving trusted influencers, positive online reviews, and strong branding, are very effective in encouraging consumers' buying intentions, especially among the younger generation in Bandar Lampung City. Keywords: Beauty Influencer, Electronic Word of Mouth, Brand Image, Purchase Intention, Skintific
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| 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 | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".