Identifikasi Sektor Unggulan Penanaman Modal Berdasarkan Keterkaitan Realisasi Investasi Dan Pertumbuhan Ekonomi Daerah: Studi Kasus Kabupaten Bandung
Bibliographic record
Abstract
Penelitian ini bertujuan mengidentifikasi sektor ekonomi unggulan dan menganalisis keselarasan realisasi investasi di Kabupaten Bandung. Menggunakan metode kuantitatif dengan analisis Location Quotient (LQ) pada data PDRB dan investasi periode 2020-2024, studi ini memetakan sektor basis (unggulan) dan non-basis. Hasil analisis menunjukkan bahwa sektor Industri Pengolahan serta Pertanian, Kehutanan, dan Perikanan merupakan sektor basis dengan daya saing regional yang kuat (LQ > 1). Namun, ditemukan adanya ketidakselarasan, di mana realisasi investasi belum teralokasi secara optimal ke semua sektor basis yang berpotensi tinggi. Beberapa sektor unggulan justru masih kekurangan investasi (under-invested). Temuan ini menyiratkan perlunya optimalisasi strategi promosi investasi oleh pemerintah daerah, dengan memprioritaskan sektor-sektor basis yang kompetitif untuk mendorong pertumbuhan ekonomi yang lebih berkelanjutan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".