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  license: apache-2.0
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- # 🇮🇩 Indonesian Regulation PDFs
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- A high-volume, web-scraped collection of **250,000+ Indonesian legal documents in PDF**, aggregated from \~350,000 public URLs. This dataset enables **legal NLP, document analysis, and regulation-aware AI applications** in Bahasa Indonesia.
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- ## Key Highlights
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- * **Format**: Archived `.zip` files (each \~5,000 PDFs)
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- * **Total Docs**: \~250K successfully downloaded
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- * **Scraped From**: Government regulation portal
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- * **Cloud Pipeline**: Scraped using **6 Google Colab nodes**, pushed directly to Hugging Face
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- * **Duration**: \~200 hours distributed scraping in total
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- * **Failures**: Some links unreachable or invalid
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- ## 🧠 Ideal For
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- * Legal document retrieval & classification
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- * Training LLMs on regulatory content
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- * Building regulation-aware assistants
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- * Multilingual or cross-domain NLP in Bahasa Indonesia
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## ⚠️ Disclaimer
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- This dataset is intended **solely for research and development**. It contains **publicly accessible legal documents** collected via ethical scraping practices.
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- No warranties are made regarding the accuracy, completeness, or legal validity of the content.
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  ## 🙏 Acknowledgments
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- * Dataset hosted on **[Hugging Face](https://huggingface.co/)** — thanks for providing an amazing platform for sharing open datasets.
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- * Data scraping powered by **[Google Colab](https://colab.research.google.com/)** — enabling scalable cloud computing to speed up data collection.
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  license: apache-2.0
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+ # 🇮🇩 Indonesian Regulation Parsed Dataset
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+ This dataset contains the **parsed content of over 250,000 Indonesian regulations**, extracted directly from PDFs at the article level **without chunking** resulting in **3.5+ million rows** representing individual articles and clauses.
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+ ## 📄 Dataset Overview
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+ * **Source**: Parsed from the original PDF collection of Indonesian regulations (\~250K documents)
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+ * **Parsed Units**: Articles, clauses, or sections as atomic units (no chunking applied)
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+ * **Size**: Over **3.5 million rows** of parsed text data
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+ * **Token Count**: Approximately **2 billion tokens** in total
 
 
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+ ## ⚙️ Processing Pipeline
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+ * **Data Flow**:
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+ 1. Pull PDFs from the **[ID\_REG repository](https://huggingface.co/datasets/Azzindani/ID_REG)**
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+ 2. Parse and extract articles using automated PDF text extraction methods
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+ 3. Push cleaned, parsed text to this Hugging Face repository
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+ * **Infrastructure**:
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+ * Utilized **6 simultaneous Google Colab instances** for parallel processing
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+ * Cloud-to-cloud architecture enables direct transfer without local storage bottlenecks
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+ * Total processing time: \~30 hours
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+ ## 🧠 Use Cases
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+ * Fine-grained legal text analysis and search
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+ * Article-level classification, summarization, or information retrieval
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+ * Training large language models on legal text with natural article boundaries
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+ * Developing Indonesian regulation compliance tools
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  ## ⚠️ Disclaimer
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+ This dataset is provided **exclusively for research and development** purposes. It contains parsed content derived from publicly available legal PDFs, and no guarantees are made regarding completeness or legal accuracy.
 
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  ## 🙏 Acknowledgments
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+ * Hosted on **[Hugging Face](https://huggingface.co/)** — a wonderful platform for open data sharing
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+ * Processing powered by **[Google Colab](https://colab.research.google.com/)** — scalable cloud resources that made fast parallel parsing possible
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