Implementation of Loan Accounting Treatment for New Members in CU. Canaga Antutn
Bibliographic record
Abstract
Research entitled Analysis of Accounting Treatment of Member Loans in CU. Canaga Antutn, aims to build a model of the accounting treatment for recording savings formation with loans and remuneration for services provided. This can formulate systems and procedures for providing productive credit to establish control and increase the productivity of CU members. This research will benefit CU because they have an accounting treatment model and credit granting system to build controls that will become a reference for CU members. The method used in this research is a survey with a qualitative approach, conducted by interviews and observing the process of accounting treatment results that have been carried out. Then it is studied to provide a solution for CU Canaga Antutn by designing a model for CU loan accounting treatment. The results of this research show that CU. Canada Antutn does not carry out journal entries, either when disbursed funds are recorded as member loans or when the loan funds are recorded as savings. Non-performing loans, both Mangala loans and productive loans, based on CU management policy, Canaga Antutn, the level of smooth payments is still considered smooth, with a range between 70% - 80%, with a limit of 60% - 90%. Mangala Loans Smooth payment rates from 2019 to 2022: 66.88%, 65.62%, 72.60% and 70.62%. Productive loans 92.88%, 92.60%, 90.72% and 95.35%. The credit disbursement control system and non-performing loans information system are still weak, and there is no analysis of the age of receivables.
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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 | 0.003 | 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 | 0.000 | 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".