Persepsi Mahasiswa Mengenai Manajemen Keuangan Pribadi Dalam Menghadapi Ancaman Resesi Ekonomi Di Indonesia
Bibliographic record
Abstract
The COVID-19 pandemic has triggered the threat economic recession in Indonesia. This condition was strengthened by the increasing number unemployed and soaring prices basic goods and fuel oil. Economic growth in Indonesia is expected to show positive numbers periodically every quarter. However, people still have to be vigilant and prepare to face the threat economic recession. Including one of them, namely students in managing finances wisely and efficiently. The purpose of this research was to determine student perceptions of personal financial management in facing the threat economic recession in Indonesia. This research method is descriptive qualitative which focuses on three indicators, namely budget preparation, emergency fund preparation, and savings measures. The population in this study were students Faculty of Economics and Business, Universitas Budi Luhur with sample 265 respondents who were taken using a purposive sampling technique. Analysis the data used in this study to measure student perceptions using score interpretation categories. The results of the study show that the budget preparation indicator is in the low category. The emergency fund preparation indicator is in the medium category. And for the indicator for saving action, it is in the low category. So that there is a low perception of students in preparing a budget, and they understand enough about the importance of emergency funds, but have not been able to take savings measures in the face threat of an economic recession in Indonesia. Suggestion the students as millennial generation can improve their financial literacy by getting used to making budgets and routines saving to achieve personal financial well-being. Keywords: Perception Student, Personal Financial Management, Recession Threat.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".