Sistem dan Metode Akuakultur Cerdas Berbasis IoT dan Kecerdasan Buatan untuk Pemantauan Budidaya Ikan Nila

Al Khwaritsmi, Muhammad Ihsan and Mahendra, Putu Indra (2025) Sistem dan Metode Akuakultur Cerdas Berbasis IoT dan Kecerdasan Buatan untuk Pemantauan Budidaya Ikan Nila. Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

Sistem Smart Aquaculture berbasis Internet of Things (IoT) dan Kecerdasan Buatan dikembangkan untuk mengatasi keterbatasan pemantauan manual pada budidaya ikan nila. Sistem ini mengintegrasikan sensor kualitas air, aktuator otomatis melalui PLC, dan protokol MQTT untuk transmisi data ke basis data cloud Supabase. Selain monitoring parameter fisik, diterapkan model computer vision YOLO11 untuk deteksi dan pelacakan perilaku ikan secara real-time dengan akurasi mAP50 mencapai 0,943. Seluruh fungsionalitas diakses melalui dashboard web berbasis Next.js yang memungkinkan kontrol manual maupun otomatis. Hasil pengujian menunjukkan bahwa sistem berhasil melakukan pemantauan lingkungan dan analisis pergerakan ikan secara komprehensif untuk mendukung efisiensi budidaya.
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A Smart Aquaculture system based on the Internet of Things (IoT) and Artificial Intelligence was developed to address the limitations of manual monitoring in tilapia farming. The system integrates water quality sensors, automated actuators controlled via a PLC, and the MQTT protocol for data transmission to a Supabase cloud database. In addition to monitoring physical parameters, a computer vision model based on YOLO11 is implemented for real-time detection and tracking of fish behavior, achieving an mAP50 accuracy of 0.943. All functionalities are accessed through a web-based dashboard developed using Next.js, enabling both manual and automatic control. Experimental results demonstrate that the system effectively performs environmental monitoring and comprehensive fish movement analysis to support aquaculture efficiency.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	Smart Aquaculture, IoT, YOLO11, MQTT.
Subjects:	S Agriculture > SH Aquaculture. Fisheries. Angling T Technology > T Technology (General)
Divisions:	Faculty of Industrial Technology > Informatics Engineering > 55201-(S1) Undergraduate Thesis
Depositing User:	Muhammad Ihsan Al Khwaritsmi
Date Deposited:	29 Dec 2025 04:20
Last Modified:	29 Dec 2025 04:20
URI:	http://repository.its.ac.id/id/eprint/129155

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