Judul: Segmentasi citra tanaman hias menggunakan metode Boykov and Kolmogorov max flow/min cut graph
Abstrak: Segmentation is an important step to improve pattern recognition. But until recently, few studies have been done yet to segment the image with complex background. This research is trying to segment the image that has a complex background. This study used Boykov and Kolmogorov max flow/min cut graph for segmentation. This method uses all the pixels to form a directed graph with two terminals. Database of 300 house plant images belong to 30 different types of house plant in Indonesia. In testing, 240 images are used and then extracted using Rotation Invariant Uniform Patterns () and performed recognition using probabilistic neural network (PNN). Results showed that accuracy increased between 8.33% to 22.22% after the segmentation.
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Judul: Ekstraksi Tekstur Citra Menggunakan Gaussian dan Multi-Block Local Binary Pattern untuk Identifikasi Tumbuhan Obat
Abstrak: Plants identification automatically is still a uses for recognizing various kinds of house plant species and medicinal plants. This research uses a method Multi-Block Local Binary Pattern (MBLBP) descriptor to extract texture feature and Probabilistic Neural Network (PNN) classifying for identifying a house plants and medicinal plants automatically. There are three kinds of MBLBP descriptor used in this research, i.e., , , , , and , . For training and testing, this research uses database of 1440 medicinal plant leaf images and 300 tree images belonging to 30 different types and obtained from Biofarmaka IPB, Cikabayan Farm, Green house Center Ex- Situ Conservation of Medicinal Plant Indonesia Tropical Forest, and Gunung Leutik. The experimental result shows that the concatination of , has the best accuracy in identifying house plants with an accuracy of 77.78%. It shows that MBLBP method is better than LBP method in identifying house plants based on the increase accuracy by 4.45%.
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Judul: Durability of Specific Immunoglobulin (Ig) Y Againts Influenza and Covid-19 in Sunscreen
Abstrak: The benefit of specific immunoglobulin Y (Ig Y) as an active ingredient in personal care products such as sunscreen has not been properly studied. Our study aims to evaluate the reliability of specific IgY against influenza and the COVID-19 virus in a sample sunscreen product. Specific IgY influenza and COVID-19 viruses were inserted in the sample sunscreen at two concentrations of 0.1% and 0.25%. Three treatments were observed: control (C) sunscreen without IgY, treatment 1 (T1) sunscreen with 0.1% IgY, and treatment 2 (T2) sunscreen with 0.25% IgY. Organoleptic observations were carried out to monitor changes in aroma, color, and texture, and sunscreen sampling was done every week for 6 weeks. The durability of IgY was evaluated using an enzyme-linked immunosorbent assay (ELISA) and a neutralization assay. Organoleptic observation from weeks 1 to 6 showed consistency in its aroma, color, and texture. Enzyme-linked immunosorbent assay and neutralization assay (NA) results of the T1 and T2 groups showed negative results except for sample T1 at week 5, which showed a positive result in the Influenza A ELISA. Based on the results, it seems that IgY concentrations of 0.1% or 0.25% were not optimal. However, this negative result might be due to low concentration of the IgY and the presence of beeswax, which inhibits IgY and causes it to dissolve in distilled water, thus preventing it from being detected in the assay.
Keyword: Immunoglobulin Y, Sunscreen, Influenza, COVID-19, Biological Activity