ANALYSIS OF EXPORT VOLUME OF INDONESIAN COFFEE TO JAPAN
Bibliographic record
Abstract
The role of international trade in the economic development of a country is quite prominent. As one source of revenue and financing for national development, this means that most national development efforts are directed at economic development. Through the process of economic development it is hoped that it can improve the standard of living of the people and create a just and prosperous society. To achieve this condition, a significant amount of funding is needed. And through international trade can generate foreign exchange for Indonesia, so that it can reduce Indonesia's dependence on other countries. Thus international trade becomes very influential for the progress of the national economy. Indonesia is one of the countries that have abundant natural resource potential. Recognizing this abundant wealth, the government and the population of Indonesia strive to exploit it with the aim of improving the welfare of society. This study aims to determine the effect of Japanese GDP, Dollar Exchange Rate and Japanese Inflation on the volume of coffee exports. In this study using secondary data in the form of annual data from 2004 - 2019 measured in time series is time series. The results of this study indicate that simultaneously the independent variables namely Japanese GDP, Dollar Exchange Rate and Inflation significantly influence the dependent variable coffee export volume. Partially, the Dollar Exchange Rate significantly influences the Coffee Export Volume, while the Japanese GDP and Japanese Inflation variables do not significantly influence the Coffee Export Volume. Keywords: Coffee Export Volume, Japanese GDP, Dollar Exchange Rate and Inflation
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".