Interaksi Faktor Eksternal dengan Siklus Finansial di Indonesia
Bibliographic record
Abstract
This study aims to interact global financial market fluctuations, commodity price fluctuations and capital flows to determine which factors interact with the cycle in Indonesia the most. The data used is secondary data from official publications, namely Bank Indonesia for data on capital flows and bank credit, the International Monetary Fund (IMF) for international commodity price index data and the global financial market valatility index (VIX). The analysis period in this study is the first quarter of 1993 to the fourth quarter of 2018. The results of the study using the correlation index show that the cycle of capital flows in Indonesia is carried out by global finance and The movement of commodity prices causes the flow of funds that enter the Indonesian economy to be largely short-term, so it tends to have acyclical interactions with bank credit to the business world and is slightly more procyclical for credit to non-business fields. Credit to non-business fields is dominated by bank credit, which is allocated to consumption credit and has a short term.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".