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All Journal Jurnal Indo-Islamika TELKOMNIKA (Telecommunication Computing Electronics and Control) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal CoreIT Applied Information System and Management MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Sosiologi Agama Building of Informatics, Technology and Science Journal of Applied Data Sciences
Nashrul Hakiem
Universitas Islam Negeri Syarif Hidayatullah Jakarta
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Journal of Applied Data Sciences

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Modeling Ramadan Hilal Classification with Image Processing Technology Using YOLO Algorithm Anggraini, Nenny; Zulkifli, Zulkifli; Hakiem, Nashrul
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.311

Abstract

This research aims to create a model for classifying hilal using the YOLO algorithm. The determination of the beginning of the month of Ramadan is an important aspect of the Islamic calendar that has an impact on the implementation of fasting. With technological advances, especially in image processing, there is potential to overcome the limitations of conventional methods currently used in hilal detection for determining the beginning of Ramadan. This research uses the prototyping method in its implementation. The dataset in this research comes from videos on the BMKG Youtube channel and images from various sources such as NASA Planetary Data System and Google Images. YOLOv5 and YOLOv8 algorithms are used to develop the object detection model. The novelty of this research is the use of the YOLO algorithm with video datasets to detect hilal to determine the beginning of the month of Ramadan and Shawwal. The best-performing model, YOLOv5m with 100 epochs and a batch size of 30, achieved a precision of 0.838 and a mAP of 0.5-0.95 of 0.735. The results indicate that YOLOv5m is more effective in hilal detection, providing a novel approach to determine the beginning of Ramadan and Shawwal with greater accuracy and consistency. This integration of advanced object detection technology with religious practice offers a significant improvement over traditional method.
Co-Authors AA Sudharmawan, AA Aang Subiyakto Al Anziy, Misyal S Al Fath, Miftahul Kahfi Amin Rois Angga Kurniawan Anggraini, Nenny Arini Arini Ariq Cahya Wardhana Aulia, Atqia Dana Indra Sensuse Dede Rosyada Denny Saputra Dzul Fadli Rahman Erma Suryani Evy Nurmiati Fetrina, Elvy Heni Pujiastuti Huda, Muhammad Qomarul Imam M Shofi Khairani, Dewi Luh Kesuma Wardhani M. Tabah Rosyadi Meinarini Catur Utami Nenny Anggraini, Nenny Nia Kumaladewi Rizal Broer Bahaweres Rohmawati, Hanung Sito Sangsawang, Thosporn Sarika Afrizal Sarika Afrizal Sarika Afrizal, Sarika Yudhanta, Satya Yuni Sugiarti, Yuni Zawawi, Khoirunnisya Zulkifli Zulkifli Zulkifli Zulkifli