ADVERTISING PAY PER CLICK (PPC) DENGAN GOOGLE ADSENSE PERSPEKTIF HUKUM ISLAM
Bibliographic record
Abstract
The internet as an effective medium in the world of business (especially in the field of marketing) from the viewpoint of the bisins to market the products produced. Various models of product offerings are conceptualized by business people issued to capture market segments. Pay per Click (PPC) is one of several programs on the internet that has the concept of giving gifts to internet users when opening advertisements submitted by advertising companies through certain sites. One dollar producer from the internet is Google Adsense. Google Adsense is a dollar-producing affiliate program issued by Google Search Engine companies by collaborating with web or blog owners in terms of Advertising. With this kind of affiliate business model, publishers (web owners or blogs) will get dollars from advertisements displayed on the web or blog. Ads displayed on the web or blog can be text or images. There are many titles for revenue generated from Google Adsense. And to find out whether or not the Muslim community is capable of following a business in the field of Advertising, such as Pay Per Click (PPC), there needs to be a study that discusses the business of Islamic Law.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.076 | 0.048 |
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".