Judul: Graph Traversing Menggunakan Teknik Branch And Bound Untuk Menemukan Senyawa Herbal Untuk Covid-19
Abstrak: Covid-19 yang disebabkan oleh virus SARS-CoV-2 sudah menjadi pandemi yang mengakibatkan krisis ekonomi dan kesehatan secara global. Terhitung sejak 26 Juni 2021, total kasus Covid-19 yang terdapat di Indonesia sudah menyentuh angka 3,13 Juta kasus. Banyaknya tanaman obat di Indonesia, dapat dimanfaatkan untuk menjadi alternatif pengobatan maupun pencegahan untuk Covid-19. Tujuan dari penelitian ini adalah melakukan Graph Traversing untuk mencari senyawa herbal terbaik yang berinteraksi dengan protein target Covid-19. Teknik yang digunakan pada penelitian ini adalah Branch and Bound. Data yang digunakan pada penelitian ini berasal dari berbagai pangkalan data yang kemudian di satukan menjadi sebuah jejaring tanaman-senyawa-protein-penyakit dan kemudian ditelusuri menggunakan tiga metode pencarian untuk mencari metode pencarian terbaik berdasarkan waktu pencarian dan kompleksitas. Strategi pencarian depth first search merupakan pilihan terbaik dalam penyelesaian masalah ini. Hasil penelitian menunjukkan tanaman seperti Alpinia Officinarum, Areca Catechu, Corydalis Yanhusuo dan Tribulus Terrestris dapat menjadi tanaman obat yang berpotensi mencegah maupun mengobati Covid-19.
Keyword: Branch and Bound, Covid-19, Graph Traversing, Drug-Target Interaction, Herbal Compound

Judul: Herbal Compound Screening for COVID-19 using Multi-Label Learning Method with Deep Neural Network
Abstrak: Wabah COVID-19 yang disebabkan oleh SARS-CoV-2 telah berlangsung selama satu tahun dan belum terlihat akan usai dalam waktu dekat. Tumbuhan herbal memiliki potensi sebagai pengobatan alternatif pada COVID-19. Dari interaksi yang dapat terjadi antara protein COVID-19 dengan beberapa senyawa, permasalahan ini dapat diformulasikan sebagai multi-label problem. Deep neural network merupakan salah satu algoritme yang dapat mengolah multi-label problem. Penelitian ini menggunakan data interaksi senyawa dengan protein signifikan SARS-CoV-2 yang akan dimasukkan ke dalam model deep neural network. Dari model tersebut, dilakukan prediksi kandidat senyawa herbal yang berinteraksi dengan protein SARS-CoV-2. Terdapat beberapa kandidat senyawa herbal hasil prediksi, ialah caffeine pada kopi, L-Theanine pada teh, coclaurine pada custard apple, carpaine pada papaya, cucurbitine pada labu, dan theobromine pada kokoa atau coklat., The COVID-19 pandemic caused by SARS-CoV-2 has been going on for a year and it doesn't look like it's over any time soon. Herbal plants have potential as an alternative treatment for COVID-19. From the interactions that can occur between the COVID-19 protein with several compounds, this problem can be formulated as a multi-label problem. Deep neural network is an algorithm that can process multi-label problems. This study uses data on interactions compound with significant SARS-CoV-2 proteins that will be included in the deep neural network model. From the model, prediction of interaction between herbal compound candidate with SARS-CoV-2 protein was made. There is some candidate from the prediction, the result is caffeine in coffee, L-Theanine in tea, coclaurine in custard apple, carpaine in papaya, cucurbitine in pumpkin, and theobromine in cocoa or chocolate.
Keyword: covid-19, deep neural network, multi-label learning, senyawa herbal

Judul: Biology and ecology of the buffalo fly, haematobia exigua de meijere (diptera:muscidae)
Abstrak: The life history of the buffalo fly was observed at room temperature of 27°-29.5°C and at a relative humidity of 48-68 percent. The eggs hatched after 17-22 hours, with an average of 18 hours. First instar larvae measured 1.25 + 0.16 mm long and 0.27 + 0.037 mm wide. reach the second larval stage. It took 6-12 hours to the second instar larvae measured 2.676 +0.187 mm long and 0.353 +0.028 mm wide. The second instar took about 12-24 hours to reach the third larval stage. The third instar measured 6.833 + 0.189 mm long and 0.919 + 0.051 mm wide. It took about 2-3 days for the third instar to become pupae. Duration of the pupal stage was about 5-7 days before the adults emerged. Under laboratory condition, the buffalo fly completed its life cycle in 9.5 to 10.5 days, whereas under field condition it took 9-14 days with an average of 10.5 days. The growth ratio which was based on the measurements of the cephalo-pharyngeal skeleton of each instar was 1.797. The preoviposition period was 8-12 days and mating usually occurred on the 6th or 7th day. The longevity of the male was 29 days, whereas it was 32 days in the female. The range of egg production under laboratory condition was between 20-139 per female fly. The belly and hind legs of the carabao were the most preferred habitat either during cloudy and cool dry or shiny and warm day. When the weather was clear and the carabao was in the shade, the flies tended to be more distributed particularly on the shoulder, dewlap, back and horns. The carabaos had relatively fewer Musca sp. and Stomoxys calcitrans than cattle; never the less carabaos had a higher infestation of buffalo fly than cattle. Oviposition occured either during the day or night but the buffalo flies were more active during the night than in the day time. The effect of various lengths of exposure time of manure in relation to the oviposition was profound. observed, the maximum number of the buffalo flies was occurred when the dung was exposed for 30 minutes. With increasing time of exposure the number and variety of insects also increase. It was evident that Sepsidae and psychodidae were the most dominant insects emerging from the dung. The number of buffalo flies also increased with increasing
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