BUSINESS FEASIBILITY ANALYSIS ON FRESH FILLET PRODUCTS GOLDBAND SNAPPER (Pristimoides multidens) PT. MATSYARAJA ARNAWA STAMBHAPURA KUPANG, EAST NUSA TENGGARA
Bibliographic record
Abstract
Indonesia, as the largest archipelagic country in the world with a vast water area, has great potential in the fisheries industry. One of the leading products that has the potential to compete in the international market is fish fillets. PT. Matsyaraja Arnawa Stambhapura, which has been engaged in the processing of fishery products since 2017, has exported fresh fillet and frozen fillet products to various countries such as Australia, Singapore, Canada, and America. To ensure the sustainability of its business, a business feasibility study is needed that includes market, technical, human resource, environmental, and financial aspects. This study aims to evaluate investment potential and business feasibility to support optimal business decision making. The purpose of this study is to determine the business feasibility of the company PT. Matsyaraja Arnawa Stambhapura. This research was conducted on February 24 - May 09, 2025. This research was conducted by means of a survey with an internship method with quantitative data sources to analyze financial aspects through certain predetermined indicators. Business analysis obtained at the company PT. Matsyaraja Arnawa Stambhapura is a net profit of IDR 389,539,726, with BEP Unit 100 units, BEP price of IDR 2,035,965, Payback Period of 1.76 months and B/C Ratio of 1.91. So this business is feasible to be established.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".