Judul: Variation of Rice Bran Quality in Dairy Cow Ration and Detection Of Counterfeiting Using Near Infrared Reflectance Spectroscopy (NIRS)
Abstrak: This study aims to create a database of rice bran and detect adulteration in rice bran using Near Infrared Reflectance Spectroscopy (NIRS) technology. The rice bran used in this study is rice brans from mills and poultry shops. This study used husks as an adulteration mixing material in rice bran with mixing levels of 25% rice bran: 75% husk, 50% rice bran: 50% husk, and 75% rice bran: 25% husk. The variables observed in this study were water content, ash content, crude fat, crude protein, and crude fiber. The analysis was carried out using proximate analysis and NIRS analysis. Calibration and validation were done using the Buchi NIRCAL 5.2 application. This study shows that the content of rice bran varies greatly and that the original rice bran from milling has better nutrient content than rice bran from the poultry shop. The accuracy of the NIRS method can be seen from the coefficient of determination, standard error, and RPD. The results of the T-test showed that the rice bran database was able to detect all parameters and was able to detect adulteration of rice bran.
Keyword: counterfeiting, NIRS, proximate analysis, rice bran

Judul: Testing of Counterfeiting Rice Bran With Rice Husk Using Image Analysis Method
Abstrak: Dedak padi sering dipalsukan dengan sekam padi giling yang dapat mengakibatkan kerugian dan penurunan produksi dari ternak. Pengujian pemalsuan dedak padi masih dijalankan secara manual yang bersifat subjektif dan kurang praktis sehingga diperlukan pengujian dengan metode image analysis berbasis Convolutional Neural Network (CNN) melalui proses analisis citra secara visual. Tujuan dari penelitian ini adalah mengukur akurasi data training, validasi, dan uji pada pemalsuan dedak padi dengan sekam menggunakan Image Analysis berbasis CNN. Penelitian ini dibagi menjadi dua perlakuan yaitu perlakuan pewarnaan menggunakan phloroglucinol dan tanpa pewarnaan. Tahapan penelitian ini terdiri atas proses pencampuran pemalsuan, pemalsuan perlakuan, pembagian data, dan pembangunan model CNN. Penelitian ini mendapatkan hasil bahwa hasil akurasi data training, data validasi, dan data uji pada perlakuan pewarnaan phloroglucinol lebih tinggi dibandingkan tanpa perlakuan pewarnaan. Namun hasil akurasi pada perlakuan pewarnaan tersebut masih jauh dari akurasi 100%, sehingga pengujian dengan metode image analisis berbasis CNN ini belum dapat digunakan, Rice bran is often adulterated with milled rice husks which can lead to losses and decreased production of livestock. Testing of rice bran forgery is still carried out manually which is subjective and less practical, so testing with image analysis methods based on Convolutional neural network (CNN) through a visual image analysis process is needed. The purpose of this study was to measure the accuracy of training, validation, and test data on rice bran fabrication with husks using Image Analysis based on CNN. This study was divided into two treatments, namely staining treatment using phloroglucinol and without staining. The stages of this research consist of the mixing process of falsification, falsification, treatment of data sharing, and CNN development model. This study found that the results of training accuracy, data validation, and data testing on phloroglucinol treatment were higher than those without treatment. However, the results of the accuracy of the treatment are still far from 100% accuracy, so testing with the CNN-based image analysis method cannot be used.
Keyword: accuracy, Convolutional Neural Network, rice bran, rice husk

Judul: Formulasi Hamiltonian untuk Menggambarkan Gerak Gelombang Soliter Dimensi Tiga di Permukaan Laut
Abstrak: Gelombang permukaan adalah gelombang yang terjadi perbedaan rapat massa antara air dan udara. Salah satu gelombang permukaan yang ditinjau adalah gelombang soliter. Formulasi gelombang soliter dilakukan dengan menggunakan formulasi Hamiltonian.
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