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p-Index From 2019 - 2024
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This Author published in this journals
All Journal Management and Sustainability Business and Sustainability
Syahdatul Maulida
SMART Indonesia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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Islamic Human Resource Management: Thematic Map and Research Cluster Syahdatul Maulida; Aam Slamet Rusydiana
Management and Sustainability Vol. 2 No. 1 (2023): Management and Sustainability
Publisher : SMART Insight

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58968/ms.v2i1.303

Abstract

This study aims to examine the development of Islamic human resource management by analyzing scholarly literature indexed in the Scopus database published from 1997 to 2023. The research methodology utilized biblioshiny-R. The findings reveal a significant increase in the number of scholarly publications in 2017, reaching a total of 17 publications. In terms of geographical distribution, Indonesia stands out as a leader with 84 documents of scholarly publications. The peak of the annual average citations occurred in 2007, with approximately 6.2 citations per year. The "Journal of Management Development" recorded the highest number of publications. The main thematic areas in scholarly publications on Islamic resource management include aspects of "Islam," "competency," and "human resource management." Additionally, the research identifies research topics based on their density and centrality, and analyzes research clusters connected through co-occurrence network analysis. It is expected that the results of this research will make a significant contribution to the understanding of the development of Islamic human resource management literature.
Mining Netizen's Opinion on Sustainable Agriculture: Sentiment Analysis of Twitter Data Syahdatul Maulida; Abrista Devi
Business and Sustainability Vol. 2 No. 1 (2023): Business and Sustainability
Publisher : SMART Insight

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58968/bs.v2i1.323

Abstract

This research aims to measure public sentiment related to sustainable agriculture on the Twitter social media platform. The research method involves the extraction and classification of tweet data using a Python Library called VADER (Valence Aware Dictionary and Sentiment Reasoner). The research utilized tweet data posted in the past one year. The results showed fluctuations and decreases in the number of tweets discussing sustainable agriculture. The location with the most tweet activity around sustainable agriculture was Brussels, Belgium, with 642 tweets during the observation period. Word cloud analysis on keywords showed that in positive sentiments, words such as "food security" and "climate change" dominated the visualization. On the other hand, in negative sentiments, words such as "farmer" and "private farmland" appeared more frequently. Overall, the majority of tweets expressed a positive attitude towards sustainable agriculture, with 68.5% positive sentiment. A total of 22.3% of tweets showed neutral sentiments, with no strong positive or negative tendencies. Only 9.1% of tweets contained negative sentiment, indicating that a small proportion of tweets expressed less favorable views towards sustainable agriculture.
Co-Authors Aam Slamet Rusydiana Abrista Devi