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p-Index From 2021 - 2026
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All Journal Jurnal Pendidikan Vokasi Indonesian Journal of Electrical Engineering and Computer Science
Mazin Abed Mohammed
University of Anbar
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Halal tourism in non-Muslim destinations: A systematic literature review of meaning contestation, misconceptions, and collaborative governance Ebtana Sella Mayang Fitri; Septi Sedyaning Hanurani; Ridho Gata Wijaya; Andris Adhitra; Mazin Abed Mohammed
Jurnal Pendidikan Vokasi Vol. 16 No. 1 (2026)
Publisher : ADGVI & Graduate School of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpv.v16i1.99992

Abstract

This study provides a systematic literature review of halal tourism in non-Muslim and multicultural destinations, focusing on rejection, misconceptions, and meaning contestation in Indonesia. Following an adapted SALSA framework and PRISMA-informed screening process, relevant studies published between 2016 and 2025 were systematically identified from major international and Indonesian academic databases. After staged screening, 23 eligible publications were synthesized through two-round thematic content analysis. Guided by symbolic threat theory, framing theory, and collaborative governance, the review identified four recurring themes: halal food and certification, destination branding and identity, regulation, and social rejection. The findings indicate that public resistance is primarily driven by misconceptions that equate halal tourism with Islamisation and threats to local cultural identity rather than opposition to Muslim-friendly services themselves. Comparative evidence from Japan, South Korea, Thailand, and Morocco further demonstrates that inclusive Muslim-friendly service approaches are more socially acceptable than normative halal destination branding. This review contributes an integrated explanatory framework linking policy framing, symbolic threat, misconceptions, and collaborative governance to explain resistance toward halal tourism in multicultural destinations. The findings provide practical guidance for promoting inclusive Muslim-friendly services, strengthening evidence-based public communication, and developing collaborative governance strategies to enhance socially sustainable tourism development.
Enhanced accuracy for heart disease prediction using artificial neural network Raniya Rone Sarra; Ahmed Musa Dinar; Mazin Abed Mohammed
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp375-383

Abstract

Making an accurate and timely diagnosis of cardiac disease is critical for preventing and treating heart failure. The accuracy of results produced by traditional machine learning (ML) algorithms is satisfactory. On the other hand, deep learning algorithms result in higher prediction accuracy. In this study, we used an artificial neural network (ANN) model to construct a deep learning diagnosis system for heart disease prediction. The developed ANN prediction model achieved 93.44% accuracy, which is 7.5% higher than a traditional ML model support vector machine (SVM). Additionally, using a simpler neural network reduced the time taken for training and classification to less than a minute.
Co-Authors Ahmed Musa Dinar Andris Adhitra Ebtana Sella Mayang Fitri Raniya Rone Sarra Ridho Gata Wijaya Septi Sedyaning Hanurani