Judul: Optimasi Arsitektur You Only Look Once Version 7 (YOLOv7) untuk Deteksi Perilaku Agresif pada Ayam Pedaging
Abstrak: Saat ini, Computer Vision telah banyak diterapkan di sektor peternakan untuk membantu pemantauan hewan ternak. Perilaku agresif merupakan salah satu permasalahan umum pada unggas berkoloni seperti ayam pedaging yang dapat berpengaruh terhadap efisiensi produktivitas dan kesejahteraan ternak. Penelitian sebelumnya menggunakan YOLOv4 berhasil membangun model deteksi perilaku agresif pada ayam pedaging namun performa deteksi model masih cukup rendah. Penelitian ini berfokus pada peningkatan presisi model dalam mendeteksi perilaku agresif pada ayam pedaging dengan mengimplementasikan arsitektur deteksi objek You Only Look Once versi ketujuh (YOLOv7) serta menerapkan penyesuaian label untuk meningkatkan kualitas data. Hasil pelatihan menggunakan arsitektur YOLOv7 menghasilkan nilai mAP (Mean Average Precision) sebesar 24,6% meningkatkan performa model YOLOv4 sebelumnya sebesar 17,1% dalam deteksi perilaku agresif. Selanjutnya, model YOLOv7 dengan penyesuaian label pada data mendapatkan nilai mAP yang lebih baik yaitu sebesar 53,7% yang menunjukkan bahwa penyesuaian label berpengaruh terhadap kinerja model., Currently, Computer Vision has been widely applied in the livestock sector to help monitor livestock. Aggressive behavior is one of the common problems in colonial poultry such as broilers which can affect productivity efficiency and livestock welfare. Previous studies using YOLOv4 have succeeded in building a model for detecting aggressive behavior in broilers, but the detection performance of the model is still quite low. This research focuses on increasing the precision of the model in detecting aggressive behavior in broilers by implementing the seventh version of the You Only Look Once object detection architecture (YOLOv7) and applying label adjustments to improve data quality. The results of training using the YOLOv7 architecture yielded a mAP (Mean Average Precision) value of 24.6%, increasing the performance of the previous YOLOv4 model by 17,1% in the detection of aggressive behavior. Furthermore, the YOLOv7 model with label adjustments on the data obtained a better mAP value of 53.7% which indicated that label adjustments had an effect on model performance.
Keyword: broiler chicken, object detection, aggressive behavior, YOLOv7

Judul: Deteksi Perilaku Makan Dan Keagresifan Pada Ayam Pedaging  Menggunakan Arsitektur Deteksi Objek You Only Look Once  (YOLOv4)
Abstrak: Permintaan pasar terhadap komoditas ayam pedaging yang tinggi menuntut peternak ayam untuk meningkatkan performa produksi. Biaya produksi dan kesejahteraan unggas menjadi aspek penting dalam daya saing industri. Untuk mengoptimalkan aspek-aspek tersebut, perilaku ayam seperti makan dan keagresifan perlu diperhatikan secara kontinu. Namun hal ini tidak praktis dilakukan sepenuhnya dengan tenaga manusia. Penerapan Precision Livestock Farming dengan Deep Learning dapat membantu memberikan keputusan secara kontinu, real-time, dan terotomasi. Pada penelitian ini diterapkan arsitektur deteksi objek You Only Look Once Version 4 (YOLOv4) untuk mendeteksi perilaku ayam makan dan keagresifan. Data yang digunakan yaitu 1.128 bounding box makan dan 881 bounding box keagresifan. Nilai mAP pelatihan model menghasilkan 73,95 % - 99,74 %, namun nilai mAP pengujian model menghasilkan 16,92 % – 32,38 %. Hal ini menunjukan bahwa pelatihan model deteksi objek masih overfitting. Pelatihan model selanjutnya perlu dilakukan pembangunan dataset lebih lanjut yang lebih relevan dan representatif serta mengurangi data yang redundan.
Keyword: broiler chicken, object detection, feeding behaviour, aggressive behaviour, YOLOv4

Judul: Hamiltonian formulation for linear waves motion in two layers fluid
Abstrak: The surface wave could be considered as a wave that separates two fluids, namely water and air. Based on this assumption, it is introduced the interfacial wave, a wave between two layers of fluid with different density. The formulation of interfacial waves motion begins with deriving the base equation of irrotational ideal fluid. Furthermore, according to irrotational fluid assumption, the base equation can be stated in velocity potential. In this derivation, the fluids domain is assumed to be restricted by rigid lid boundary conditions, both at the upper and lower limit. Therefore, the interfacial waves motion can be explained in a hamiltonian formulation. In the hamiltonian formulation, total energy is defined as the sum of kinetic and potential energy. The hamiltonian system is obtained from reduction of kinetic energy by using the Dirichlet Neumann Operator. The resulted kinetic energy equation is nonlinear. Therefore, this form is linearized by first part of the Taylor expansion. This linearization gives a dispersion relation of linear wave. Based on this dispersion relation, the phase speed of the linear wave depends on the density ratio of the two layers fluid.
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