Judul: Sifat Fisis dan Mekanis Kayu-Polietilen Glikol dari Jenis Sengon, Manii, dan Gmelina
Abstrak: The timbers of fast growing species products of the community forests is one of the raw material supplier to the industrial timber in indonesia. The objective of this research is to obtain the physical and mechanical properties of sengon (Falcataria mollucana Miq), manii (Maesopsis eminii Engl.), and gmelina (Gmelina arborea Roxb.) that impregnated with PEG 400. Manufacture of impregnated wood in this research were using the vacuum pressure method by means of impregnation poly-ethylene glycol (PEG) 400 with 100% concentration. Sample and testing methods of physical and mechanical properties refer to the British Standard (BS) 373: 1957. Impregnation of wood with PEG 400 affect moisture content, density, shrinkage and swelling, static bending strength, shear strength, and hardness. Physical properties of PEG- wood are better than untreated wood (control), but the mechanical properties of PEG-wood are lower compared to untreated wood. Sengon woods have higher polymer loading compared to gmelina and manii, it is affected by wood anatomical structure.
Keyword: Bogor Agricultural University (IPB), impregnation, gmelina, sengon, manii, Poly Ethylene Glycol

Judul: Physical, Mechanical Properties and Durability of Impregnated Sengon Wood by Nano Silica orignated from Betung Bamboo Leaves
Abstrak: Sengon (Falcataria moluccana Miq.) merupakan jenis kayu cepat tumbuh yang memiliki beberapa kelemahan, yaitu berat jenis, kekuatan, keawetan, kerapatan dan stabilitas dimensi yang rendah. Penelitian ini bertujuan untuk menganalisis pengaruh perlakuan impregnasi menggunakan monoethylene glycol (MEG) dan nano silika daun bambu betung terhadap sifat fisis, mekanis dan keawetan kayu sengon. Salah satu metode modifikasi kayu adalah impregnasi. Proses impregnasi memiliki keunggulan yaitu dapat meningkatan kerapatan dan kekerasan kayu dengan memasukkan polimer ke dalam struktur kayu. Larutan impregnasi yang digunakan yaitu kontrol (tanpa perlakuan), MEG, MEGSilika 0.5% dan MEGSilika 1%. Proses impregnasi dimulai dengan pemberian vakum 0.5 bar selama 60 menit dan dilanjutkan dengan pemberian tekanan 2.5 bar selama 120 menit. Hasil penelitian menunjukkan perlakuan impregnasi MEG dan nano silika berpengaruh nyata dan meningkatkan nilai weight percent gain (WPG), kerapatan, perubahan warna (ΔΕ), MOE, MOR, kekerasan dan persentase mortalitas rayap tanah Coptotermes curvignathus serta menurunkan persentase kehilangan berat pada kayu sengon. Secara keseluruhan perlakuan MEGSilika 1% merupakan perlakuan yang paling optimum untuk kayu sengon yang berumur 5 tahun, Sengon (Falcataria moluccana Miq.) is fast growing wood species which has inferior characteristics i.e. low specific gravity, strength, durability, density and dimensional stability. The objective of this study was to analysis the effect of monoethylene glycol (MEG) and nano silica originated from betung bamboo leaves impregnation treatment on physical, mechanical properties and durability of sengon wood. One of wood modification methods is impregnation. Impregnation process could increase the wood density and hardness by introducing polymer into wood structure. The impregnation solution were consisted of water treated (untreated), MEG, MEGSilika 0.5% and MEGSilika 1%. The impregnation process was initiated by applying 0.5 bar of vacuum for 60 min and followed by 2.5 bar of pressure for 120 min. The results showed that MEG and nano silica impregnation treatment had significant effect on and increased weight percent gain (WPG), density, color changes (ΔΕ), MOE, MOR, hardness and mortality percentage of termite Coptotermes curvignathus and decreased weight loss percentage. MEGSilika 1% was the optimum treatment for of 5-year-old sengon wood.
Keyword: daun bambu betung, impregnasi, keawetan, nano silika, sengon, betung bamboo leaves, durability, impregnation, nano silica

Judul: Quantum Convolutional Neural Network on Image XRay Thorax as an Alternative for COVID-19 Diagnosis
Abstrak: Penelitian ini bertujuan untuk menemukan alternatif diagnosis COVID-19 menggunakan citra toraks X-Ray dengan metode Quantum Convolutional Neural Network. Data yang digunakan adalah data original dan data hasil augmentasi. Augmentasi yang dilakukan adalah augmentasi kontras, kecerahan dan rotasi. Parameter selanjutnya adalah pemilihan jumlah epoch yaitu 3, 5, 10, 15, 20, 25, 30, atau 35. Input data pada penelitian ini adalah 4 × 4 piksel citra toraks X-Ray yang selanjutnya ditransformasi ke dalam bentuk sirkuit 16 qubit. Data dalam bentuk sirkuit tersebut akan diproses dengan metode Quantum Convolutional Neural Network, dimana arsitektur Quantum Convolutional Neural Network ini terdiri dari layer quantum convolution, layer quantum pooling dan layer quantum neural network. Pemodelan tersebut memiliki hasil tertinggi pada penggunaan data original dan pemilihan epoch 25 yang menghasilkan akurasi 77%, sensitivitas 43% dan spesifisitas 82%., This research aims to find an alternative diagnosis of COVID-19 using thorax X-Ray images with the Quantum Convolutional Neural Network method. The data used is the original data and the augmented data. Augmentasi carried out is contrast, brightness and rotation augmentation. The next parameter is the selection of the number of epochs 3, 5, 10, 15, 20, 25, 30, or 35. The input data in this research is a 4 × 4 pixel X-Ray thorax image which is then transformed into a 16 qubit circuit. The data in the form of circuit will be implemented into a Quantum Convolutional Neural Network, where the architecture of this Quantum Convolutional Neural Network consists of a quantum convolutional layer, a quantum pooling layer and a quantum neural network layer. The modeling has the highest result using the original data and selecting epoch 25 which produces 77% accuracy, 43% sensitivity and 82% specificity.
Keyword: citra toraks, COVID-19, data augmentasi, QCNN, qubit