DEMAND MANAGEMENT AND PRODUCTION CAPACITY IN SERVICE SECTOR MSMEs IN BATAM CITY
Bibliographic record
Abstract
This study aims to find out what methods Irepairgo MSMEs use in accepting the request process, how Irepairgo MSMEs in handling service requests that increase in a period to remain effective and timely, Irepairgo MSMEs demand patterns, and the advantages of Irepairgo MSMEs from other MSMEs. This research uses qualitative methods by using several interview and observation techniques. The results showed that the performance of the iRepair Go MSMEs compared to the iRepairgo MSMEs increased in the second quarter of each year. It can be seen from the demand graph for services from iRepairgo appears to have increased and improved from the 3rd quarter of 2020 to the 2nd quarter of 2021 before experiencing a slight decline again in the 3rd quarter of 2021 and rising again in the 4th quarter of 2021. It is also suspected that demand was helped to rise after consumers and enthusiasts of products from Apple were able to get the Apple products they wanted through the iBox online store (PT. Data Citra Mandiri), which is one of the licensees as the first distributor of Apple products in Indonesia, and was then followed by one of the subsidiary of PT. Mitra Adiperkasa Tbk (MAP group), namely Digimap, which is also the official distributor of Apple products.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".