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All Journal Musyarakah: Journal of Sharia Economics (MJSE) eJEBA
Asykarulloh, Azam
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Religion Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Covid-19 dan The Stock Reaction Of Islamic Banking In Asia Asykarulloh, Azam; Sultoni, Hasan
Musyarakah: Journal of Sharia Economic (MJSE) Vol 4, No 2 (2024): October
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/mjse.v4i2.9373

Abstract

The number of COVID-19 cases that hit Asia also put pressure on the economy and turmoil in several stock markets. This study aims to see the reaction of Islamic banking stocks in Asia to the announcement of COVID-19 as a global pandemic by WHO. This research uses an event study method with an observation period of 10 days after and before the event day. Data were obtained through the stock trading website, and 43 banking samples from 11 countries were observed. Data analysis used One-Sample T-Test, Paired Sample T-Test, One Sample Wilcoxon Signed Rank Test, and Paired Sample Wilcoxon Signed Rank Test with the help of SPSS 21.0 tools. The results showed that there was a significant AAR around the event days. And there is a difference in CAAR before and after the event day. These results were accompanied by a negative CAAR value after the event period, which confirmed that Islamic banking stocks in Asia responded negatively to the announcement of COVID-19 by WHO. The robustness test results show that ASEAN is the most reacted region compared to the GCC, South Asia, and other areas.
MINING PUBLIC OPINIONS ON URBAN GREEN SPACES IN MAGELANG: BIG DATA SENTIMENT AND TOPIC MODELING FOR SDGS-ORIENTED POLICY Dewi, Ivana Rosediana; Asykarulloh, Azam; Utami, Cahyaning Budi
e-Journal Ekonomi Bisnis dan Akuntansi Vol. 13 No. 1 (2026): e-JEBA Volume 13 Number 1 Year 2026
Publisher : e-Journal Ekonomi Bisnis dan Akuntansi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/e-jeba.v13i1.60003

Abstract

Urban Green Spaces (UGS) play a crucial role in improving environmental quality, fostering social interaction, and enhancing the well-being of urban communities. In Magelang City, Indonesia, a growing small city, understanding public perceptions of UGS is essential to ensure their effective development and to align with Sustainable Development Goal (SDG) 11: Sustainable Cities and Communities. This study employs an AI-based approach to evaluate public sentiments and identify key discussion themes by applying big data analytics to user-generated reviews from Google Maps. Python-based text mining techniques were utilized, with the Valence Aware Dictionary for Sentiment Reasoning (VADER) used for sentiment classification and Latent Dirichlet Allocation (LDA) applied for topic modeling. Results show that public perception is predominantly positive, emphasizing cleanliness, comfort, aesthetic value, and accessibility. Negative sentiments, although fewer, highlight issues in facility maintenance, limited amenities, safety, and spatial accessibility. These findings provide actionable implications for policymakers by offering evidence-based justification for future investments, responsive design strategies, and continuous monitoring of UGS quality from a citizen-centered perspective. Contributing to more inclusive, safe, and sustainable urban development aligned with SDG 11.7.
Co-Authors Dewi, Ivana Rosediana Sultoni, Hasan Utami, Cahyaning Budi