Society's Perspectives on Contemporary Islamic Law in Indonesia through Social Media Analysis Technology
A Preliminary Study
Bibliographic Data
| ID | 22344052 |
|---|---|
| Authors | Dian Sa’adillah Maylawati (0000-0002-1193-3370, Sunan Gunung Djati State Islamic University Bandung), Siah Khosyi’ah (0000-0002-8585-5301, Sunan Gunung Djati State Islamic University Bandung), Achmad Kholiq (IAIN Syekh Nurjati Cirebon) |
| Year | 2022 |
| Volume | 12 |
| Issue | 1 |
| Pages | 14-31 |
| Publication date | 2022-01-13 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Islamic Khazanah (JOURNAL) |
| Journal identifiers | ISSN: 2302-9366 • E-ISSN: 2302-9781 |
| Publisher | Sunan Gunung Djati State Islamic University of Bandung (PUBLISHER) |
| DOI | 10.15575/ijik.v12i1.15865 |
| OpenAlex | W4220908286 |
| Language | EN |
| Citations received | 1 |
| References cited | 11 |
The social, cultural, and technological developments of society are unavoidable. This has an impact on the development of Islamic Law, which keeps all Muslim activities in the right corridor. Contemporary Islamic law, known as Contemporary Islamic Law, has also developed to answer new societal problems. Various views on Contemporary Islamic Law in solving multiple issues certainly reap various responses from the community and scholars. These views are often conveyed through social media such as Youtube, Instagram, Facebook, and Twitter. Therefore, this article aims to discuss a preliminary study of text analysis techniques used to find out the views of the community and Ulama on Contemporary Islamic Law issues computationally and automatically. This initial study reviews the methods and techniques that will be used, namely the Indonesian National Work Competency Standards (SKKNI) methodology for data science. This study will also use a sentiment analysis approach, topic modeling, and pattern analysis to find out people's views on issues of Contemporary Islamic Law through social media. The algorithm used for sentiment analysis is the Multinomial Naà ̄ve Bayes Classifier (MNBC), for topic modeling is Latent Dirichlet Allocation (LDA), while for pattern analysis using the Prefix-projected Sequential Pattern Mining (PrefixSpan) algorithm. The model generated from sentiment analysis, topic modeling, and pattern analysis will be evaluated by measuring the confusion matrix, coherence value, and silhouette coefficient value. In addition, analysis and interpretation of the model results will be carried out in-depth qualitatively by involving the views and thoughts of Islamic Law experts
Data science · Geography · Islam · Latent Dirichlet allocation · Political science · Sentiment analysis · Sharia · Social media · Social science · Sociology · Topic model · Computer Science · Islamic Finance and Communication · Law · Legal and Social Justice Studies · Legal Studies and Policies · Artificial Intelligence
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The mediums and the messages
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Handbook of Natural Language Processing
Doing social media analytics
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0.25 |
| Citation span | 2022 - 2022 (1) |
| Citation velocity | historical |
| Highly cited | No |