ARTIFICIAL INTELLIGENCE TO OPTIMIZE THE ROLE OF NOTARIES IN RESOLVING LAND INHERITANCE DISTRIBUTION BASED ON CUSTOMARY LAW

Authors

  • Davina Malem Peraten Ketaren Universitas Borobudur

DOI:

https://doi.org/10.46799/ijssr.v4i11.1109

Keywords:

Notary, Land Inheritance, Customary Law, Artificial Intelligence, Legal Technology

Abstract

The distribution of land inheritance often poses challenges, particularly within the context of customary law that varies by region. The role of notaries, recognized legally to draft authentic deeds in accordance with Article 16, Paragraph (1), letters a and b of Law No. 2 of 2014 on Amendments to Law No. 30 of 2004 on Notary Positions, is crucial in providing legal certainty and preventing disputes among heirs. In this era of technological advancement, artificial intelligence (AI) can assist notaries in expediting and simplifying the resolution of land inheritance issues more efficiently while adhering to applicable customary law provisions. The purpose of this research is to analyse the role of notaries in the resolution of land inheritance distribution under customary law and to explore the potential utilization of artificial intelligence in assisting this process. The research method used is normative juridical, using a statutory approach and an analytical approach. The research shows that artificial intelligence (AI) can assist notaries in document verification, heir identification, and the application of complex customary law. AI accelerates the process and reduces the potential for disputes, but it requires regulatory adjustments and increased technological literacy among notaries and the public. Artificial intelligence (AI) has significant potential to optimize the role of notaries in resolving land inheritance under customary law by accelerating processes, improving accuracy, and ensuring fairness. However, the successful implementation of AI requires clear regulations and collaboration between the government, legal institutions, and customary communities.

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Published

2024-11-20