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Implementing the haversine formula for detecting societal issues and delivering relevant preaching content
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Implementing the haversine formula for detecting societal issues and delivering relevant preaching content

Kurniawan, R

Implementing the haversine formula for detecting societal issues and delivering relevant preaching content

Kurniawan, R ; Sharif University of Technology | 2024

86 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/IConEEI64414.2024.10748204
  3. Publisher: IEEE , 2024
  4. Abstract:
  5. The effectiveness of Islamic preaching is often hindered by the need for localized data on societal issues, which leads to lectures that may not address the community's specific needs. This study seeks to bridge this gap by developing a system that provides relevant preaching outlines tailored to issues detected within a 1 km radius of a mosque. The system incorporates data from 185 mosques and is enhanced by integrating societal issues as a feature. The Haversine formula was employed for precise distance calculations to identify nearby issues accurately. Blackbox testing verified that the system functions correctly. In addition, response time experiments showed an average time of 0.17 seconds. This result highlights the system's overall efficiency in delivering quick responses. Furthermore, a user acceptance test involving eight Islamic preachers revealed high satisfaction with the system's ease of understanding, as indicated by a mean score of 4.75. These findings suggest that the system effectively supports preachers in delivering contextually relevant preaching and enhances the impact of their preaching efforts by aligning them with the specific concerns of the communities. This innovative approach marks a significant step forward in using geospatial intelligence for religious outreach, with future developments planned to integrate AI to generate dynamic content for various Islamic occasions. © 2024 IEEE
  6. Keywords:
  7. Geospatial intelligence ; Haversine formula ; Islamic preaching ; Societal issues detection ; Black-box testing ; Black boxes
  8. Source: Proceedings of the International Conference on Electrical Engineering and Informatics ; 2024 , Pages 73-78 ; 21556830 (ISSN); 979-833154079-1 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/10748204