The Tendencies of Cryptocurrency Policies in Indonesia
Bibliographic record
Abstract
Cryptocurrency has set intriguing and innovative trends in investment amidst the fluctuating global economy following government policies. This research aims to investigate the trends of policies of cryptocurrency in Indonesia, seen from the perspective of taxation and investment laws. Low tax charged in Indonesia is seen as relaxation by investors and cryptocurrency users, while the trends in legal policies concerning investment are experiencing hyper regulations in legislative products set to assure investors, in comparison to those of other countries. These trends attract some attention from investors and cryptocurrency users from abroad. This research is a unique offering that will illustrate which countries are suitable and friendly for businesspeople to carry out crypto business activities. The methodology used in this study is normative research with a conceptual approach and comparative law. The research results are expected to shed light on foreign investors wishing to invest their money in cryptocurrency businesses by considering the low tax from the perspective of current taxation law in Indonesia compared to those in Canada, the United States, and Singapore. According to the details of taxation in Canada, the United States, and Singapore, it is obvious that Indonesia gives ease to foreign cryptocurrency investors in Indonesia from the aspect of taxation law. The countries compared seem to charge very high taxes for cryptocurrency users and businesses in investment cryptocurrency. This comparison gives easier access to foreign investors to invest their assets for the development of cryptocurrency businesses and companies in Indonesia by considering the amounts of taxes imposed on cryptocurrency businesses and users. Indonesia makes it easier for foreign cryptocurrency investors in Indonesia compared to Canada, the United States, and Singapore from a tax law perspective. In terms of investment regulations, Indonesia has broader laws and regulations compared to other countries, where the investment process involving cryptocurrency businesses in Indonesia receives sufficient attention from these laws and regulations.KEYWORDS: Cryptocurrency, Investment Law, Taxation Law.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".