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: Integrasi MobileNet-SSD dan Isolation Forest untuk Implementasi Sistem Deteksi Anomali Pergerakan Ayam Berbasis Web
Abstrak: Dalam usaha ternak ayam broiler, kesejahteraan hewan merupakan salah satu aspek yang perlu diperhatikan peternak. Aspek dalam kesejahteraan hewan diantaranya adalah freedom from hunger or thirst (kebebasan dari kelaparan dan haus) dan freedom from pain, injury or disease (kebebasan dari rasa sakit, luka dan penyakit). Proses pemberian pakan secara terus menerus mengakibatkan meningkatnya massa ayam broiler, membuat ayam broiler menjadi kesulitan bergerak untuk mengambil makanan maupun air, yang mengakibatkan ayam broiler menjadi sakit kemudian mati. Tersedianya sistem yang dapat mendeteksi kesulitan bergerak pada ayam broiler akan memudahkan peternak dalam memantau pergerakan ayam broiler dari kejauhan. Dalam penelitian ini, deteksi ayam yang kesulitan bergerak dilakukan melalui integrasi model deteksi objek MobileNet-SSD dan algoritma deteksi anomali isolation forest dari penelitian sebelumnya. Integrasi dilakukan menggunakan bahasa pemrograman Python, diuji menggunakan video dengan kombinasi resolusi dan frame per second (FPS) tertentu, kemudian diimplementasikan menjadi sebuah aplikasi web menggunakan framework Flask. Hasil analisis integrasi menunjukkan bahwa semakin besar resolusi dan FPS video masukan, maka waktu inferensi dan waktu eksekusi dari sistem hasil integrasi menjadi semakin besar dan diestimasi meningkat secara linear., In the broiler farming business, animal welfare is an aspect that needs to be considered by breeders. Aspects of animal welfare include freedom from hunger or thirst and freedom from pain, injury, or disease. The process of continuous feeding results in broiler chicken's mass increase, making it difficult for them to move to get food and water, resulting in their sickness and death. The availability of a system that can detect the movement difficulty of the broiler chickens will make it easier for farmers to monitor the movement of broiler chickens from afar. In this study, the detection of chickens that had difficulty moving was carried out by integrating the MobileNet-SSD object detection model and the isolation forest anomaly detection algorithm from previous studies. Integration is carried out using Python programming language, tested using video with a combination of resolution and frame per second (FPS), then implemented into a web application using the Flask framework. The integration analysis shows that the greater the resolution and FPS of the input video, the greater the inference and execution time. Both times are also estimated to increase linearly.
Keyword: animal welfare, anomaly detection, broiler chicken, object detection, web application

Judul: Karakteristik Kimia Kayu Reaksi Ulin (Eusideroxylon zwageri T. et B.)
Abstrak: Reaction wood which formed in hardwood generally has a lower klason lignin content, higher acid soluble lignin content, and higher syringil unit than opposite wood. Ulin wood (E. zwageri) contains high klason lignin and low acid soluble lignin contents which closed to lignin characteristic of softwood. This experimental aimed to study the difference of chemical characteristic of reaction wood (klason lignin content, acid soluble lignin content, and lignin monomer composition) and polysaccharides content which formed in E. zwageri stem. Visually, the reaction wood part was formed in upper side of leaning stem. Klason lignin content in reaction wood part was lower (32.71%) than opposite wood part (33.74%). However, the lowest lignin content was found in the side wood part (28.15%). Lignin of E. zwageri was composed by syringyl and guaiacyl monomer with average of syringil to guaisyl ratio 0,2. Acid soluble lignin content in E. zwageri was very low (0.69%) that positively correlated with the proportion of syringil unit in lignin. Polysaccharide content of reaction wood part (63.66%) was higher than opposite wood part (62.88%), but the highest content polysaccharides presented in the side wood part (64.19%).
Keyword: Polisaccharide, syringil-guaiasyl ratio, lignin, E. zwageri, reaction wood