Artificial Intelligence Usage in Zakat Optimization

Authors

  • Fajar Nugraha Rumah Zakat, Indonesia
  • Sendi Permadia Rumah Zakat, Indonesia
  • Aditya Rahmat Gunawan Rumah Zakat, Indonesia
  • Erip Saeful Rumah Zakat, Indonesia

DOI:

https://doi.org/10.37706/iconz.2019.144

Keywords:

Big Data, Artificial Intelligence, Zakat, Rumah Zakat

Abstract

The development of big data and Artificial Intelligence is a challenge and also opportunity in managing zakat. Dramatically changes of technology could impact on social life and employment throughout the world, including zakat institutions. This study discusses changes in the management of zakat in 4.0 industrial revolution era, and how big data and Artificial Intelligence take over part of amil duties. The method used in this research is qualitative with a constructivistic paradigm. The research subject of this study is Rumah Zakat as the national zakat institution, with the object of research on the change in management of zakat from zakat 1.0 era to the era of zakat 4.0 and any AI technology that can take over part of amil duties. There is a change in the management of zakat from the zakat 1.0 era to the zakat 4.0 era which is certainly influenced by the development of industrial revolution. The presence of AI technology has taken over part of the amil duties at Rumah Zakat, which is in charge of serving both muzakki and mustahiq. With the presence of various artificial intelligence and big data devices, made the tasks of amil are simpler, more time-saving, and more efficient.

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Author Biographies

Fajar Nugraha, Rumah Zakat

Research & Program Development Department

Sendi Permadia, Rumah Zakat

Research & Program Development Department

Aditya Rahmat Gunawan, Rumah Zakat

Research & Program Development Department

Erip Saeful, Rumah Zakat

Health and Education Program Department

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Published

2019-11-18

How to Cite

Nugraha, F., Permadia, S., Gunawan, A. R., & Saeful, E. (2019). Artificial Intelligence Usage in Zakat Optimization. Indonesian Conference of Zakat - Proceedings, 14–24. https://doi.org/10.37706/iconz.2019.144

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