cover
Contact Name
Hamid
Contact Email
numera@uinsaizu.ac.id
Phone
+628818762897
Journal Mail Official
numera@uinsaizu.ac.id
Editorial Address
Jl. A. Yani No. 40 Purwokerto 53126 Jawa Tengah - Indonesia Telp. 0281-635624 Fax. 0281-636553
Location
Kab. banyumas,
Jawa tengah
INDONESIA
Jurnal Nusantara Raya
ISSN : -     EISSN : 29634970     DOI : 10.24090/jnr
Jurnal Nusantara Raya publishes articles with aim and scope: 1. Language teaching 2. Literature teaching 3. Learning Indonesian Language and Literature 4. Study of Indonesian, Archipelago, and Malay Languages 5. Study of Indonesian literature 6. Comparative Literature Study 7. Comparative Linguistics
Arjuna Subject : Umum - Umum
Articles 1 Documents
Search results for , issue "vol. 5 no. 3 (2026)" : 1 Documents clear
SMART ZAKAT YANG INKLUSIF DAN BERBAWASAN SYARIAH: INTEGRASI KECERDASAN BUATAN, BIG DATA, HAD KIFAYAH, DAN MAQĀṢID AL-SHARĪ‘AH UNTUK MENINGKATKAN KETEPATAN SASARAN PENDAYAGUNAAN ZAKAT Rahmini Hadi
Jurnal Nusantara Raya Vol. 5 No. 3 (2026)
Publisher : Lembaga Kajian Nusantara Raya (LK Nura)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/m3xana04

Abstract

Digital transformation creates new opportunities for zakat management through Artificial Intelligence (AI), Big Data, machine learning, and Explainable Artificial Intelligence (XAI). Nevertheless, current Smart Zakat studies tend to treat targeting accuracy as a technical classification problem, while justice, Had Kifayah, maqāṣid al-sharī‘ah, and digital exclusion remain insufficiently integrated. This study aims to develop a Shariah-Aware and Inclusive Smart Zakat framework through an integrative literature review of studies published mainly during 2022–2026 on AI, Big Data, digital zakat, machine learning, XAI, Had Kifayah, maqāṣid al-sharī‘ah, and poverty alleviation. The review identifies three major gaps: the dominance of beneficiary classification, limited operationalization of shariah-based targeting accuracy, and the risk of excluding digitally invisible beneficiaries. The proposed model integrates Big Data profiling, machine learning, Had Kifayah, maqāṣid al-sharī‘ah, fairness auditing, XAI, human validation, and outcome prediction.

Page 1 of 1 | Total Record : 1