• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.665-673
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• 2021

The phenomenon of sharia-based tourism development has now become a necessity for the people of Indonesia and even for the global community. Therefore, we need rules and regulations that govern it, both rules relating to normative sharia and regulations governing implementation in a positive legal manner. The purpose of this research is to describe halal tourism in Indonesia in terms of the Indonesian Council of Ulama National Sharia Board (DSN-MUI) fatwa and the government regulation. This research is a conceptual review that uses literature research methods sourced from authoritative journals, books and documents and is still relevant to the study of halal tourism. The results showed that the large number of public requests for halal tourism visits in Indonesia resulted in the need for normative and positive regulation that regulates. Finally, the MUI issued and stipulated fatwa Number: 108/DSN-MUI/IX/2016 regarding the implementation of tourism based on sharia principles and West Nusa Tenggara Regional Regulation Number. 2 of 2016 concerning Halal Tourism. Overall, the halal tourism indicator according to the DSN-MUI fatwa Number: 108/DSN-MUI/X/2016 and West Nusa Tenggara Regional Regulation Number. 2 of 2016 the content is almost the same and interrelated with one another. The only difference is in the use of the term "sharia tourism" in the DSN- MUI fatwa while the content in the regional regulation (PERDA) uses the term "halal tourism".

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.281-291
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• 2021

The Islamic jurisprudential legal system represents an essential component of the Islamic religion, that governs many aspects of Muslims' daily lives. This creates many questions that require interpretations by qualified specialists, or Muftis according to the main sources of legislation in Islam. The Islamic jurisprudence is usually classified into branches, according to which the questions can be categorized and classified. Such categorization has many applications in automated question-answering systems, and in manual systems in routing the questions to a specialized Mufti to answer specific topics. In this work we tackle the problem of automatic categorisation of Islamic jurisprudential legal questions using deep learning techniques. In this paper, we build a hierarchical deep learning model that first extracts the question text features at two levels: word and sentence representation, followed by a text classifier that acts upon the question representation. To evaluate our model, we build and release the largest publicly available dataset of Islamic questions and answers, along with their topics, for 52 topic categories. We evaluate different state-of-the art deep learning models, both for word and sentence embeddings, comparing recurrent and transformer-based techniques, and performing extensive ablation studies to show the effect of each model choice. Our hierarchical model is based on pre-trained models, taking advantage of the recent advancement of transfer learning techniques, focused on Arabic language.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.346-356
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• 2022

The jurisprudential legal rules govern the way Muslims react and interact to daily life. This creates a huge stream of questions, that require highly qualified and well-educated individuals, called Muftis. With Muslims representing almost 25% of the planet population, and the scarcity of qualified Muftis, this creates a demand supply problem calling for Automation solutions. This motivates the application of Artificial Intelligence (AI) to solve this problem, which requires a well-designed Question-Answering (QA) system to solve it. In this work, we propose a QA system, based on retrieval augmented generative transformer model for jurisprudential legal question. The main idea in the proposed architecture is the leverage of both state-of-the art transformer models, and the existing knowledge base of legal sources and question-answers. With the sensitivity of the domain in mind, due to its importance in Muslims daily lives, our design balances between exploitation of knowledge bases, and exploration provided by the generative transformer models. We collect a custom data set of 850,000 entries, that includes the question, answer, and category of the question. Our evaluation methodology is based on both quantitative and qualitative methods. We use metrics like BERTScore and METEOR to evaluate the precision and recall of the system. We also provide many qualitative results that show the quality of the generated answers, and how relevant they are to the asked questions.