Judul: Implementasi Strongsort Dengan Yolov5 Untuk Pendeteksian Posisi Bangkai Ayam Dari Data Video
Abstrak: Dalam peternakan ayam, jika bangkai ayam tidak dibuang dengan cepat dari kandang ayam, akan meningkatkan resiko tersebarnya penyakit unggas. Oleh karena itu, suatu metode yang dapat mendeteksi bangkai ayam secara cepat akan sangat berguna untuk peternak ayam. Penelitian ini mengajukan untuk menggunakan Object Tracking sebagai metode pendeteksian bangkai ayam. Model Object Tracking yang digunakan adalah StrongSORT yang dibantu dengan metode Object Detection YOLOv5. Data video dari 8 kamera CCTV kandang ayam Fakultas Peternakan akan digunakan sebagai data pelatihan dan pengujian. Object Tracking akan dijalankan terhadap data tersebut. Akan disimulasikan data yang akan merepresentasikan data bangkai ayam. Hasil penelitian mendapatkan akurasi klasifikasi terbaik terendah 92% dan tertinggi 99%, In poultry farming, if carcasses are not quickly disposed of, they will increase the risk of spreading diseases. Therefore, a method that can quickly detect chicken carcasses will be very useful to poultry farmers. This research proposes to use Object Tracking as said method. StrongSORT is chosen as the object tracking model with the help of YOLO v5 as an Object Detection model. Video Data from 8 CCTV from Faculty of Animal Science’s chicken shed will be used as training and testing data. Object Tracking will be executed on said data. Data will be simulated which will represent chicken carcass data. The result of the research the best accuracy of classifiers at worst is 92% and at best 99%
Keyword: Chicken Carcass, Object Tracking, StrongSORT

Judul: Multi-Object Tracking (MOT) Algorithm Modification for Poultry Behavior Anomaly Detection
Abstrak: Peningkatan konsumsi daging ayam mendorong pesatnya pertumbuhan perusahaan ternak unggas di Indonesia. Hal ini tentunya harus diimbangi dengan tingkat kesejahteraan ternak yang baik. Salah satu dari lima prinsip kebebasan hewan (5F) adalah kebebasan dari rasa sakit, luka, dan penyakit (freedom from pain, injury, and diseases). Ayam yang tidak berpindah tempat dalam waktu yang lama kemungkinan menderita sesuatu dalam tubuhnya. Untuk memperhatikan masing-masing ternak setiap saat akan menghabiskan banyak waktu dan tenaga peternak, oleh karena itu dibutuhkan cara untuk melakukan pengawasan terhadap ternak. Salah satu cara yang bisa dilakukan adalah dengan mengembangkan sistem pengawasan pergerakan ayam menggunakan algoritme Multi-Object Tracking (MOT). Algoritme MOT merupakan metode penelusuran objek yang terdiri atas tahap pendeteksian objek dan penelusuran objek. Dalam penelitian sebelumnya digunakan metode hibrida yang hanya melakukan pendeteksian objek setiap beberapa frame dan melakukan penelusuran objek dalam rentang waktu tersebut secara bergantian dengan tahap pendeteksian objek. Metode ini menghasilkan skor Multi-Object Tracking Precision (MOTP) sebesar 60.4%. Sementara dalam penelitian ini digunakan metode sekuensial, dimana program melakukan tahap pendeteksian objek dan penelusuran objek secara berurutan yang menghasilkan skor MOTP sebesar 87.64% dan untuk mendeteksi ayam yang tidak bergerak dalam waktu lama (data anomali) digunakan algoritme pencarian anomali Isolation Forest. Hasil dari penelitian ini masih dapat diperbaiki dengan menggunakan model deteksi objek khusus ayam broiler dan integrasi agar dapat dilakukan pengawasan dalam waktu nyata., The increase in consumption of chicken meat encourages the rapid growth of poultry farming in Indonesia, which has to be balanced with decent animal welfare care and implementation. One of the Five Freedom principle is freedom from pain, injury, and diseases. Chickens that don't move for a long time are more likely to feel uncomfortable with the environment or with their own body. Observing each poultry for every second will waste a lot of time and effort of the farmer, therefore it is necessary to have a way to monitor the poultry. One way that can be done is to develop a chicken movement monitoring system using the Multi-Object Tracking (MOT) algorithm. The MOT algorithm is an object tracking method consisting of object detection and object tracking. In previous studies, a hybrid method was used which only detects objects every few frames and tracks objects in that period alternately with the object detection stage. This method produces a Multi-Object Tracking Precision (MOTP) score of 60.4%. Meanwhile, in this study a sequential method is used, where the program performs object detection and object tracking stage sequentially, which results in a MOTP score of 87.64% and to detect chickens that have not moved for a long time, the Isolation Forest anomaly search algorithm is used. The results of this study can still be improved by using a specialized object detection model for broilers and integration so that real-time monitoring can be carried out.
Keyword: multi-object tracking, deteksi objek, deteksi anomali, kesejahteraan hewan

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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