Implementasi Pengolahan Citra Menggunakan Metode YOLO pada Security Robot dibidang Pertanian
I will put the dimension here
Abstract
Greenhouse merupakan salah satu bentuk solusi pertanian modern untuk membudidayakan tanaman yang tidak sesuai dengan iklim tropis, khususnya di Indonesia. Namun, pembangunan greenhouse itu sendiri memerlukan biaya yang cukup mahal. Sumber daya perangkat elektronik yang diperoleh dari panel surya digunakan untuk menyediakan pasokan listrik kepada perangkat elektronik seperti exhaust fan, panel surya, dan perangkat lainnya. Sayangnya, sering kali terjadi kasus-kasus orang yang tidak bertanggung jawab melakukan pencurian atau merusak properti dan tanaman di area sekitar greenhouse, yang dapat merugikan petani. Penelitian ini bertujuan untuk mendeteksi objek (manusia) yang melintas di sekitar greenhouse, peneliti menggunakan teknik pengolahan citra sebagai mata robot untuk mendeteksi manusia di mana objek selain manusia diabaikan. Metode yang digunakan dalam penelitian ini adalah YOLOv3-tiny, yang merupakan metode pembaharuan dari Convolutional Neural Network (CNN). YOLOv3-tiny akan melakukan prediksi terhadap objek yang akan dideteksi dengan bounding box sebagai output. Selanjutnya, YOLOv3-tiny akan memilih bounding box yang paling sesuai dalam memprediksi objek. Hasil pengujian menunjukkan bahwa robot mampu mendeteksi objek berupa manusia, serta menghitung akurasi kinerja model.
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