Application of Artificial Intelligence in Automatic Crescent Moon Detection System Using Teachable Machine Model on Web Platform - Walhidayah, Ravik; Ismail, Ismail (University of Muhammadiyah Sumatera Utara, 2025)
The issue of the visibility of the new moon (hilal) often becomes a recurring debate, especially during two major Islamic occasions: the determination of the beginning of Ramadan and the start of Dhu al-Hijjah for Eid al-Adha. In the practice of rukyat (moon sighting), claims of hilal sightings are frequently made without strong or objective evidence. Therefore, the utilization of artificial intelligence technology, particularly in the field of image classification, presents a potential solution to improve the accuracy and objectivity of the moon sighting process. This research employs an image classification model trained using the Teachable Machine platform. The trained model is then integrated into a websitesite developed using HTML, CSS, and Python, and hosted via the github service. Through this websitesite, rukyat observers can upload photos of the sky captured during moon observation. The AI model will then analyze the uploaded image to determine whether the hilal is visible or not. This system is expected to serve as a scientific and modern tool to support the moon sighting process.