MSMEs Move Up a Class: Sustainable Strategies to Encourage MSMEs to Enter the International Market
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Blitar City is the largest producer of jimbe drums in East Java, and even in Indonesia. The market segment for jimbe drum products is China and Canada. However, not all jimbe drum craftsmen in Blitar City are able to access the export market. This study aims to (a) Identify the characteristics of SMEs in the Jimbe drum industry in Blitar City (b) Describe the obstacles faced by jimbe drum craftsmen to move up to the export market (c) Develop strategies to encourage SMEs in the jimbe drum industry in Blitar City to move up in a sustainable manner. The type of research is a qualitative case study. The subjects of the study were jimbe drum craftsmen in Sentul Village, Blitar City, Head of the Cooperatives and MSMEs Office of Blitar City, Head of the Trade and Industry Office, Head of Sentul Village, Blitar City. Data collection was carried out by direct interviews with research subjects, observation and documentation. Triangulation of methods and data sources was carried out to obtain accurate data. Data analysis using the Miles, Huberman and Saldana (2024) formula and SWOT analysis. The results of the study showed that there are 2 types of Jimbe drums MSMEs in Sentul village, namely craftsmen and collectors, who do not yet have an association/ cooperative to accommodate the aspirations of craftsmen. The obstacles faced revolve around the difficulty of accessing capital and obtaining raw materials. Based on the SWOT analysis, the appropriate strategy for sustainable upgrading is to first improve the organization, help access capital and increase international marketing reach through partnerships.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it