Judul: Multi-Object Tracking (MOT) Algorithm Implementation for Poultry Behavioral Analysis
Abstrak: Ayam merupakan salah satu hewan ternak yang paling banyak dikonsumsi di Indonesia. Selain itu kesadaran akan kesejahteraan hewan (animal welfare) juga semakin meningkat di dalam maupun luar negeri. Dengan meningkatnya persaingan dagang antar peternak dan kebutuhan untuk memenuhi standar yang berlaku, dibutuhkan cara untuk melakukan efisiensi jumlah dan jadwal pemberian pakan serta pengawasan terhadap ternak ayam. Analisis kebiasaan ternak ayam dapat dilakukan untuk mengatasi hal tersebut. Penelitian ini bertujuan untuk mengimplementasikan algoritme Multi-Object Tracking untuk deteksi pergerakan banyak ternak ayam sebagai landasan awal pembuatan model analisis perilaku ternak ayam. Model yang dihasilkan berhasil menelusuri pergerakan banyak objek dengan tingkat presisi 60.4%.
Keyword: ayam, deteksi objek, multi-object tracking, pergerakan

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: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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