PERAN TAMPILAN PRODUK, KEAMANAN DAN KEMUDAHAN PADA KEPUTUSAN BERTRANSAKSI MENGGUNAKAN JASA PENGIRIMAN SHOPEE
Bibliographic record
Abstract
Abstract This research aimed to test and analyze the role of product display, security and ease of transaction decisions using Shopee's shipping services. This research was conducted in the Surakarta area. The object of this research is consumers who have transacted using the Shopee application. The population in this study were consumers who had shopped using the Shopee application who had made transactions at the end of 2019. The sample determination process was carried out based on consumer experience in using the Shopee application. Furthermore, it was ensured that the consumers who were the samples of this study met the specified criteria and were willing to fill out the questionnaire. If they were not willing and do not meet the criteria, then the consumer was skipped and then researcher looked for other consumers who met the sample criteria. By using this technique, not all populations in this study had the same opportunities as research samples. In this study the sample was 56 respondents. This study resulted in a regression equation, it can be seen that product appearance, security and convenience have a positive effect on the decision to transact using Shopee's shipping services. The results of the t-statistical test show that product appearance, security and convenience partially have a significant effect on the decision to transact using Shopee's delivery service Keywords: Product Display, Security and Ease, Transaction Decision.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 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".