The Forecasting Analysis of Profit on Astra Companies List on Indonesia Stock Exchange (IDX)
Bibliographic record
Abstract
This research aims to analyze the profit forecasting using the weighted moving average method then compare the pattern between Astra companies listed on IDX (Indonesia Stock Exchange). The research method use is quantitative descriptive with secondary data of profit in the 2018-2022 period that provides quarterly. The result for this research shows the highest forecasting of profit on PT Astra International Tbk occurring in the third quarter in 2023 with the amount of 20,970. While the lowest forecasting occurred in first quarter in 2023 with the amount of 9,410. While the lowest forecasting occurred in first quarter in 2023 with the amount of 13,529. The highest forecasting of profit on PT United Tractors Tbk occurs in the third quarter in 2023 with the amount of 13,738,446. While the lowest forecasting occurred in first quarter in 2024 with the amount of 5,584,042. and the highest forecasting of profit on PT United Tractors Tbk occurs in the second quarter in 2023 with the amount of 50,707. While the lowest forecasting occurred in the third quarter in 2024 with the amount of 22,496.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".