Assessing the Impact of Current Ratio, Return On Assets, and Debt To Equity Ratio on Financial Distress of PT Jasa Marga (Persero) Tbk Over the 2013-2022
Bibliographic record
Abstract
This study aims to examine the Financial Distress of PT Jasa Marga (Persero) Tbk through its financial performance. The analysis explores into the challenges associated with infrastructure development, particularly toll roads, wherein the high levels of financing and capital requirements lead to a significant increase in corporate debt. If it is not managed properly, this could potentially result in bankruptcy for the company. Using the Ordinary Least Square (OLS) method to analyze the issue, three internal factor variables were employed: Current Ratio (CR), Return On Assets (ROA), and Debt To Equity Ratio (DER).Based on the research findings, PT Jasa Marga (Persero) Tbk experienced financial distress from the second quarter of 2020 to the second quarter of 2021. Return on Assets (ROA) and Debt to Equity Ratio (DER) emerged as the primary factors influencing financial distress, whereas Current Ratio (CR) had no significant impact on it. With the influence of ROA and DER, PT Jasa Marga (Persero) Tbk faces a high risk concerning its ability to repay debts, attract new investments, or maintain a healthy financial balance. This could lead to a decline in the company's value, difficulties in accessing new sources of funding, or even bankruptcy. PT Jasa Marga (Persero) Tbk must consistently strive to improve its financial performance with careful attention.Keyword: Financial Distress; Current Ratio; Return on Assets; Debt to Equity Ratio; Ordinary Least Square (OLS).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".