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 and mechanical properties of poly ethylene glicol and polystyrene wood from mangium (acacia mangium willd.) and pine (pinus merkusii jungh. et de vries)
Abstrak: Impregnasi kayu merupakan salah satu teknologi modifikasi kayu untuk meningkatkan sifat fisis dan mekanis. Tujuan penelitian ini adalah untuk membandingkan sifat fisis dan mekanis kayu Mangium dan Tusam dengan pemberian Poly Ethylene Glicol (PEG) dan Polystyrene. Bahan baku yang digunakan yaitu kayu mangium dan tusam. Impregnasi kayu dilakukan dengan menggunakan metode vakum tekan yaitu dengan pengisian bahan kimia seperti poli etilen glikol (PEG) dan polistiren ke dalam kayu dengan proses polimerisasi pemanasan. Jenis pengujian sifat fisis dan mekanis yang dilakukan mengacu pada British Standard (BS) 373:1957 meliputi kadar air, kerapatan, kembang susut, keteguhan lentur statis, keteguhan patah, keteguhan geser, dan kekerasan. Hasil pengujian menunjukkan nilai rata-rata kadar air pada kayu mangium berkisar 7.26-10.17% dan kayu tusam berkisar 8.75-15.64%. Nilai rata-rata kerapatan pada kayu mangium berkisar 0.44-0.55 g/cm3 dan kayu tusam berkisar 0.70-0.96 g/cm3. Nilai rata-rata kembang susut pada kayu mangium berkisar 1.40-5.53% dan kayu tusam berkisar 0.61-3.96%. Nilai rata-rata keteguhan lentur statis pada kayu mangium berkisar 44678-74924 kg/cm2 dan kayu tusam berkisar 43754-69938 kg/cm2. Nilai rata-rata keteguhan patah pada kayu mangium berkisar 337-589 kg/cm2 dan kayu tusam berkisar 251-615 kg/cm2. Nilai rata-rata keteguhan geser pada kayu mangium berkisar 40-90 kg/cm2 dan kayu tusam berkisar 34-104 kg/cm2. Nilai rata-rata kekerasan pada kayu mangium berkisar 356-583 kg/cm2 dan kayu tusam berkisar 201-717 kg/cm2. Pemberian polistiren dan poli etilen glikol baik pada kayu mangium maupun tusam dapat meningkatkan kadar air, kerapatan, keteguhan lentur statis, dan kekerasan tetapi kembang susut, keteguhan patah dan keteguhan geser menurun., Impregnation of timber is one of the wood modification technology to improve the physical and mechanical properties. The research objective it was to compare physical and mechnical properties on mangium and pine timber impregnated with poly ethylene glicol (PEG) and polystyrene. The materials used were mangium and pine. Impregnation used vacuum pressure method which was by filling chemical substances of poly ethylene glicol (PEG) and polystyrene through by thermal polimerisation on the timber. The test impregnation wood conducted by refer the (British Standard (BS) 373:1957) comprised moisture content, density, shrinkage swelling, stiffness, static bending strength, shear strength and hardness. The result showed the average value of the moisture content ranged 7.26-10.17% for mangium and 8.75-15.64% for pine. The average value of the density ranged 0.44-0.55 g/cm3 for mangium and 0.70-0.96 g/cm3 for pine. The average value of the shrinkage swelling ranged 1.40-5.53% for mangium and 0.61-3.96% for pine. The average value of the stiffness ranged 44678-74924 kg/cm2 for mangium and 43754-69938 kg/cm2 for pine. The average value of static bending strength ranged 337-589 kg/cm2 for mangium and 251-615 kg/cm2 for pine. The average value of shearing strength ranged 40-90 kg/cm2 for mangium and 34-104 kg/cm2 for pine. The average value of hardness ranged 356- 583 kg/cm2 for mangium and 201-717 kg/cm2 for pine. The addition of polystyrene and poly ethylene glycol into mangium or pine are increasing the moisture content, density, stiffness and hardness, but shrinkage swelling, static bending strength and shearing strength are decreased.
Keyword: mangium, poli etilen glikol, polistiren, sifat fisis dan mekanis, tusam

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