Strategi Pengembangan Potensi Sumber Daya Alam untuk Meningkatkan Perekonomian di Kecamatan Karang Baru, Kabupaten Aceh Tamiang
Bibliographic record
Abstract
Abstract. Kecamatan Karang Baru has abundant natural resources, particularly in the agriculture, plantation, fisheries, and livestock sectors. This study aims to identify the leading commodities with potential to develop the local economy and formulate strategies for the development of natural resources in Kecamatan Karang Baru, Aceh Tamiang. A quantitative approach was used, incorporating LQ, Shift Share (SS), and SWOT analysis. The results indicate that leading commodities such as coffee, guava, breadfruit, duck, gourami, and tilapia have great potential for development through improved productivity, product diversification, and market access enhancement. Additionally, non-leading commodities also hold potential for development by applying efficient agricultural technologies, diversifying products, and expanding market promotion. The study recommends strategies including collaboration between institutions, cooperation between governments, product quality improvement, and infrastructure strengthening to foster sustainable local economic growth. Abstrak. Kecamatan Karang Baru memiliki sumber daya alam yang melimpah, terutama di sektor pertanian, perkebunan, perikanan, dan peternakan. Penelitian ini bertujuan untuk mengidentifikasi komoditas unggulan yang berpotensi mengembangkan ekonomi daerah dan merumuskan strategi pengembangan sumber daya alam di Kecamatan Karang Baru, Kabupaten Aceh Tamiang. Pendekatan kuantitatif digunakan dengan analisis LQ, Shift Share (SS), dan SWOT. Hasil penelitian menunjukkan bahwa komoditas unggulan seperti kopi, jambu biji, sukun, itik, gurame, dan bawal memiliki potensi besar untuk dikembangkan melalui peningkatan produktivitas, diversifikasi produk, dan penguatan akses pasar. Selain itu, komoditas non-unggulan juga berpotensi untuk berkembang dengan penerapan teknologi pertanian efisien, diversifikasi produk, dan promosi pasar yang lebih luas. Penelitian ini merekomendasikan strategi berupa kolaborasi antar lebaga, kerja sama antar pemerintah, peningkatan kualitas produk, dan penguatan infrastruktur untuk mendorong pertumbuhan ekonomi lokal yang berkelanjutan.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".