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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) The Indonesian Journal of Computer Science
M Abrar Masril
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Sistem Pengawasan Berbasis IoT pada Robot Vision Untuk Peningkatan Keamanan Perimeter di Industri Batam Caniago, Deosa Putra; Muhammad Jufri; M Abrar Masril
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4476

Abstract

Batam City faces significant security challenges alongside rapid industrial growth, making the need for effective surveillance systems in industrial areas urgent. This research developed a surveillance robot utilizing Internet of Things and computer vision technologies to enhance perimeter security in industrial zones. The robot is equipped with Arduino as the controller, a Pixy2Cam camera for object detection, and a WiFi module for remote connectivity. Testing results indicate that the robot can detect individuals wearing safety gear in 0.2 seconds and achieves a detection success rate of 100% under ideal conditions. The developed controller application using MIT App Inventor also displays real-time images, allowing for rapid responses to potential threats. This research demonstrates that the developed surveillance robot effectively enhances monitoring in the Batam industrial area.
Application of YOLOv8 Algorithm for Coral Reef Disease Detection as an Effort to Prevent Marine Habitat Damage in Batam Rifa'atul Mahmudah Burhan; Refli Noviardi; M Abrar Masril; Firmansyah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6062

Abstract

Research in 2019 in Batam City showed that out of 19 coral reef fisheries support facilities, 16 were declared not good. Coral reef damage increased from 36.28% to 39.44%. This is due to the threat of coral reef damage due to international shipping lane areas, human activities such as destructive fishing, pollution, sedimentation, and global warming. These threats can cause coral diseases such as black band disease (BBD), brown band disease (BrB), Bleaching Coral, and yellow band disease (YBD). The Underwater Photo Transect (UPT) method collects data in the field in the form of underwater photos and analyzes them to obtain quantitative data. This method has a weakness, namely the low level of accuracy in detecting coral reef diseases. This study proposes coral reef disease detection using the YOLO model YOLO8l, YOLO8x, and YOLO8m. The results of the model evaluation test with a threshold value of 0.5 to 0.95 against the test data show that the three models can detect coral reef diseases with an accuracy of 99%. These results prove that the YOLOv8 model in this study is suitable for the real-time detection of coral reef diseases to replace the Underwater Photo Transect (UPT) method, which has low accuracy. Applying the YOLOv8 method will help Prevent Marine Habitat Damage in Batam City.
Co-Authors Caniago, Deosa Putra Firmansyah Muhammad Jufri Noviardi, Refli Rifa'atul Mahmudah Burhan