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: Implementasi Model Yolov4 untuk Pemantauan Perilaku Agresif Ayam Broiler Berbasis Website
Abstrak: Produktivitas daging ayam merupakan hal yang penting dalam menjaga pasokan daging ayam sebagai komoditas penting dalam negeri. Pemantauan terhadap perilaku agresif ayam merupakan salah satu upaya menjaga kesejahteraan ayam. Penelitian untuk mengamati perilaku ayam telah dilakukan dengan bantuan deep learning yaitu YOLOV4 yang menghasilkan model deteksi perilaku agresif ayam. Penelitian ini bertujuan mengimplementasikan model tersebut dalam bentuk website dengan menggunakan framework Flask dengan library OpenCV. Pengguna dapat mengunggah video yang ingin dilakukan deteksi perilaku agresif lalu sistem akan melakukan deteksi dengan YOLOv4 dan menghasilkan video yang telah ditandai. Pengujian implementasi pada web dilakukan dengan memasukkan beberapa jenis video yang memiliki resolusi dan durasi berbeda. Hasil uji menunjukkan bahwa deteksi video berhasil dilakukan dan ditampilkan keterangan tambahan berupa average confidence dan durasi waktu proses. Dapat disimpulkan bahwa, semakin besar resolusi dan durasi video masukan maka semakin tinggi nilai confidence yang didapat dan semakin lama proses deteksinya., The chicken meat productivity is important to maintain the chicken meat supply as an important domestic commodity. The monitoring of the chicken’s aggressive behavior is an effort to maintain their welfare. Many research to observe chicken behavior has been carried out with the help of deep learning, namely YOLOv4 which produces a model to detect the chicken’s aggressive behavior. This study aims to implement the model in the form of a website. It was created using the Flask framework with the OpenCV library. A user can upload video that he wants to detect aggressive behavior, then the system will detect them with YOLOv4 and produce video that have been tagged. Implementation testing on the web is carried out by entering several types of videos that have different resolutions and durations. The test results show that video detection was successful and additional information is displayed in the form of average confidence and processing time duration. In conclusion, the larger the resolution and duration of the input video, the higher the confidence value obtained and the longer the detection process.
Keyword: Aggressive Behavior, Broiler Chicken, Object Detection, Flask, YOLOv4

Judul: Physical Caracterutie of Lipstick Using Beeswax at Different Concentrations.
Abstrak: Lipstick is one of the cosmetic base as pigment dispertion on fat. Lipstick is used to colour lips with artistic touch so it can grown up estetic in order to colouring face. Purpose of the lipstick beside for decorative effect, it can protect lips from weather influence and dirty air too. Lipstick formulation use from base, perfume, antioxidant and pigment. Base can grouping became oil, fat and wax. Commonly waxes to use for lipstick are carnauba wax, candelilla wax and ozokerite wax. Beeswax which has been extraction from the comb of the hive is often contaminated by other substances. Therefore, beeswax usually melted, filtered also bleached in order to get lipstick that have good shine and physic characteristic. The objective of this research is to seen function influence of beeswax which bleached by 1.5% activated charcoal at 15%, 25%, 35% and 45% concentrations on lipstick quality resulted.
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