Judul: Image Classification Model of Foot and Mouth Disease  in Cow Using Convolutional Neural Network
Abstrak: Penyakit Mulut dan Kuku (PMK) pada sapi merupakan ancaman serius bagi industri peternakan di Indonesia yang dapat mempengaruhi kesehatan dan produktivitas ternak. Penelitian ini bertujuan mengembangkan aplikasi sederhana berbasis website untuk klasifikasi citra sapi sehat dan terinfeksi PMK menggunakan CNN dengan arsitektur VGG-16 dan MobileNet-V2. Dataset yang digunakan terdiri dari 197 citra, yaitu citra kelas sehat dan pmk. Proses penelitian meliputi pengumpulan dataset, pra-proses data, pembuatan model CNN, hyperparameter tuning, evaluasi model, dan implementasi sistem berbasis website. Model terbaik untuk arsitektur VGG-16 menggunakan optimizer Adam, learning rate 0,01, dan epoch 50, mencapai akurasi training 0,941, akurasi validasi 0,937, dan akurasi testing 0,905 dengan precision 0,846, recall 1,000, dan F1-score 0,917. Untuk MobileNet-V2, konfigurasi terbaik menggunakan optimizer Adam, learning rate 0,001, dan epoch 100, memberikan akurasi model pada training 0,988, akurasi model pada validasi 0,947, dan akurasi model pada testing 0,952 dengan precision 1,000, recall 0,910, dan F1-score 0,952. Penelitian ini telah berhasil membangun aplikasi sederhana berbasis web untuk klasifikasi citra sapi sehat dan PMK menggunakan framework Flask. Aplikasi ini bekerja berdasarkan sistem voting dari dua model, yaitu VGG-16 dan MobileNet-V2 yang memberikan hasil identifikasi yang sama jika kedua model menghasilkan output yang sama., Foot and Mouth Disease (FMD) in cow is a serious threat to the livestock industry in Indonesia that can affect the health and productivity of livestock. This research aims to develop a simple web-based application for image classification of healthy and FMD-infected cow using CNN with VGG-16 architecture and MobileNet-V2. The dataset used consists of 197 images, namely healthy and FMD class images. The research process includes dataset collection, data pre-processing, CNN model building, hyperparameter tuning, model evaluation, and website-based system implementation. The best model for VGG-16 architecture using Adam optimizer, learning rate 0.01, and epoch 50, achieved training accuracy 0.941, validation accuracy 0.937, and testing accuracy 0.905 with precision 0.846, recall 1.000, and F1-score 0.917. For MobileNet-V2, the best configuration uses Adam optimizer, learning rate 0.001, and epoch 100, giving model accuracy on training 0.988, model accuracy on validation 0.947, and model accuracy on testing 0.952 with precision 1.000, recall 0.910, and F1-score 0.952. This research has successfully built a simple web-based application for the classification of healthy and FMD cow images using the Flask framework. This application works based on a voting system of two models, namely VGG-16 and MobileNet-V2 which gives the same identification result if both models produce the same output.
Keyword: klasifikasi citra, Convolutional Neural Network, MobileNet-V2, Penyakit Mulut dan Kuku, VGG-16

Judul: Status of Foot and Mouth Disease Antibodies in Dairy Cattle in The North Cianjur Cattle Cooperative Region
Abstrak: Penyakit mulut dan kuku (PMK) adalah penyakit infeksi pada hewan berkuku belah dan merupakan penyakit re-emerging di Indonesia. Kasus PMK mulai terjadi pada ternak sapi perah di wilayah Cianjur Utara pada bulan Mei 2022, kemudian program vaksinasi PMK mulai dilakukan di wilayah ini sejak bulan Juni 2022. Monitoring keberadaan antibodi setelah vaksinasi penting dilakukan guna mengevaluasi efektivitas program vaksinasi. Penelitian ini bertujuan menentukan status antibodi PMK pada sapi perah di wilayah Cianjur Utara dengan kriteria berikut: pernah terinfeksi-divaksin satu kali, tidak pernah terinfeksi-divaksin dua kali, dan pernah terinfeksi-belum divaksin. Dua puluh lima sampel susu individu dikoleksi dan dianalisa keberadaan antibodi PMK dengan metode enzyme linked immunosorbent assay (ELISA) kompetitif. Hasil ELISA menunjukkan bahwa 2 sampel susu asal sapi pernah terinfeksi-divaksin satu kali positif memiliki antibodi PMK, sedangkan sampel lainnya negatif antibodi PMK. Hasil ini mengindikasikan bahwa antibodi PMK lebih banyak terbentuk pada individu yang pernah terinfeksi dan divaksin, dibandingkan individu yang tidak pernah terinfeksi dan divaksin dua kali maupun individu yang pernah terinfeksi dan belum divaksin. Selain itu, hasil ini juga memperlihatkan bahwa sampel susu individu dapat digunakan sebagai sampel alternatif non-invasif untuk monitoring antibodi PMK setelah vaksinasi karena pengambilan sampelnya relatif lebih mudah dilakukan dan aspek kesejahteraan hewan terpenuhi., Foot and mouth disease (FMD) is an infectious disease in cloven hooves and is a re-emerging disease in Indonesia. FMD cases began to occur in dairy cattle in the North Cianjur region in May 2022, then the FMD vaccination program began in this region in June 2022. Post-vaccination antibody monitoring is important to evaluating the effectiveness of vaccination programs. This study aims to determine the FMD antibody status in dairy cattle in the North Cianjur region with the following criteria: infected-vaccinated once, never infected-vaccinated twice, and infected-not vaccinated. Twenty-five milk samples were collected and analyzed for the presence of FMD antibodies using a competitive enzyme-linked immunosorbent assay (ELISA). The ELISA results showed that 2 milk samples from dairy cattle that have been infected-vaccination once were positive for FMD antibodies, while the other samples were negative. These results indicate that more FMD antibodies are formed in individuals who have been infected and vaccinated, compared to individuals who have never been infected and vaccinated twice or individuals who have been infected and have not been vaccinated. Moreover, these results showed that individual milk samples can be used as a non-invasive alternative sample for monitoring FMD antibodies after vaccination because the sampling is relatively easy and animal welfare aspects are met.
Keyword: antibodies, enzyme linked immunosorbent assay (ELISA), foot and mouth disease (FMD), milk samples, vaccination

Judul: Pembuatan Sel Surya Berbasis Film Ferroelektrik Barium Strontium Titanate (Ba0,5Sr0,5TiO3)
Abstrak: Growth of films Ba0,5Sr0,5TiO3 (BST) 1 M has been done with variation of annealing in hold time 8 hours, 15 hours, 22 hours, and 29 hours at constant temperature 8500C, above Si (100) substrate p-type, by using the sol-gel process method which followed with spin coating process at 3000 rpm for 30 seconds. Optics spectroscopy shows that BST film solar cells with annealing hold time 8 hours, 15 hours, and 22 hours, works effectively in wavelength ≥ 700 nm absorption range. Yet for sample with annealing hold time about 29 hours effectively absorb in ≤ 700 nm wavelength range. It obtained BST film refractive index at range 2.0 to 7.0 to wavelength range ±370-870 nm. Band gap BST film value based on annealing hold time 8 hours, 15 hours, 22 hours, and 29 hours respectively 2.60 eV; 3.12 eV: 3.24 eV, and 2.66 eV. Electrical conductivity value which obtained, indicate that the BST film is classified as semiconductor material with conductivity order 10-5-10-4 S / cm. The result of I-V photovoltaic characterization shows the BST film potentially to be a solar cells device with efficiency according to the annealing hold time 8 hours, 15 hours, 22 hours, and 29 hours in a row are 2.68x10-5%, 3.51x10-5%, 4.53x10-5% and 3.22x10-5%
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