DAMPAK PEMBANGUNAN SENTRA IKM MENGGUNAKAN DANA ALOKASI KHUSUS (DAK) TERHADAP BANYAKNYA INDUSTRI KECIL MENENGAH DI INDONESIA
Bibliographic record
Abstract
Pembangunan Sentra Industri Kecil Menengah (Sentra IKM) merupakan salah satu program kebijakan Pemerintah yang bertujuan untuk pengembangan dan penumbuhan Industri Kecil Menengah (IKM) baru serta untuk percepatan pemerataan pemerataan industri di seluruh Indonesia. Pembangunan Sentra IKM ini dilakukan menggunakan Dana Alokasi Khusus (DAK) Fisik. Penelitian ini bertujuan menganalisis dampak program pembangunan Sentra IKM tahun 2016-2019 terhadap peningkatan banyaknya Industri Kecil Menengah di Indonesia dengan menggunakan Data Industri Mikro Kecil, Data Industri Besar Sedang serta Data Status Operasional Sentra IKM dan menggunakan metode fixed effect difference in difference (FE-DID). Hasil penelitian ini menunjukkan bahwa operasional Sentra IKM di kabupaten/kota di Pulau Sulawesi, Jawa, Nusa Tenggara, Kalimantan, Maluku dan Papua memiliki dampak signifikan terhadap peningkatan banyaknya IKM pada jenis industri pangan, kerajinan dan alat angkut. Namun dampak tersebut berbeda pada jenis industri logam dan alat mesin pertanian di Pulau Jawa dan Sumatera akibat adanya perbedaan kondisi wilayah dan manfaat produktivitas pada masing-masing jenis industri. Hasil penelitian ini menunjukkan bahwa Program Pembangunan Sentra IKM efektif dalam menumbuhkan IKM baru di luar Pulau Jawa dan Sumatera pada jenis industri padat karya
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".