HALAL CERTIFICATION IN INDONESIA: Study of Law Number 6 of 2023 on Job Creation
Bibliographic record
Abstract
The enactment of the Job Creation Law in approval of Government Regulation in Lieu of Law No. 2 of 2022, which became Law No. 6 of 2023 on Job Creation, has resulted in significant changes in halal certification in Indonesia, which is the main focus of this research. This study aims to discuss halal certification in Indonesia following the implementation of the omnibus law on job creation. The author adopts a standardized legal approach and a descriptive-analytical approach through literature research. The research findings indicate that comprehensive legislation is expected to streamline the halal certification process in Indonesia. There are important changes regarding halal certification in Law No. 6 of 2023 compared to Law No. 11 of 2020 on Job Creation. This regulation aims to accelerate and enhance efficiency in halal certification, ensuring legal certainty and fostering trust among Muslim consumers in halal products. The growth of micro-enterprises in terms of expediting halal certification shows positive trends. The research contributes new perspectives and original findings that positively impact problem-solving or theory development in the advancement of halal certification in Indonesia.Lahirnya UU Cipta Kerja sebagai pengesahan Peraturan Pemerintah Pengganti Undang-Undang Nomor 2 Tahun 2022 menjadi Undang-Undang Nomor 6 Tahun 2023 tentang Cipta Kerja telah menghasilkan perubahan signifikan dalam sertifikasi halal di Indonesia. Tujuan dari penelitian ini adalah untuk membahas sertifikasi halal di Indonesia pasca penerapan omnibus law penciptaan lapangan kerja. Penulis mengadopsi pendekatan hukum standar dan pendekatan deskriptif-analitik melalui penelitian literatur. Temuan penelitian menunjukkan bahwa peraturan yang komprehensif diharapkan dapat merampingkan proses sertifikasi halal di Indonesia. Ada perubahan penting terkait sertifikasi halal pada UU No 6 Tahun 2023 dibandingkan dengan UU No 11 Tahun 2020 tentang Cipta Kerja. Regulasi ini bertujuan untuk mempercepat dan meningkatkan efisiensi dalam sertifikasi halal, menjamin kepastian hukum dan menumbuhkan kepercayaan konsumen muslim terhadap produk halal. Pertumbuhan usaha mikro dalam hal percepatan sertifikasi halal menunjukkan tren yang positif. Penelitian ini menyumbangkan perspektif baru dan temuan orisinal yang berdampak positif terhadap pemecahan masalah atau pengembangan teori dalam kemajuan sertifikasi halal di Indonesia.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".