Judul: Pengaruh penambahan fumed silica, pencernaan dan suhu vulkanisasi lanjut terhadap sifat fisik vulkanisat lateks
Abstrak: Indonesia is a country which has the largest rubber plantation in the world. In 2004, Indonesia had 3,26 million hectare area for rubber plantation. Its larger than Thailand's rubber plantation which has only 2 million hectare. Nevertheless, Indonesia produce natural rubber smaller than Thailand. Indonesia only produce 2,08 million tons while Thailand can produce 3,06 million tons in the same time. One of the way to raise and stimulate production of rubber plantation is develop industry natural rubber manufacturing in Indonesia.
Keyword: 

Judul: Pemanfaatan Lateks Karet Alam Sebagai Bahan Pemodifikasi Aspal Untuk Meningkatkan Mutu Perkerasan Jalan Aspal.
Abstrak: Indonesia is the second largest producer of natural rubber in the world after Thailand. Indonesia's natural rubber production in 2007 reached 2.55 million tons per year. However, Indonesia's natural rubber production has decreased due to the global crisis that occurred in 2008. One of the sectors directly affected by the crisis is the automotive industry which is the largest consumer of natural rubber in the world. On the other hand, economic growth will increase the traffic load in terms of quantity, weight and speed. The burden of heavy traffic, road surface temperature reaches 70oC, high rainfall and the poor drainage, causing the road can be easily damaged. Therefore, paving way’s modification is required to fulfill those needs, one with the latex modified asphalt. The purposes of this study were to determine the effect of types and additional doses of latex in the asphalt toward penetration value and softening point which affecting the quality of asphalt pavement and to get the best mixture of asphalt to improve the quality of asphalt road pavement. This research methodology consiststed of two stages, namely preparation of raw materials (determination of the nature and characteristics of latex and latex depolymerization process) and the main research (the mixing process of latex into the asphalt and testing). Experimental design used in this study was Complete Random Factorial design with two replications for each treatment. Factors that influence were types and additional doses of latex rubber in the asphalt with each level of 8 and 3. There were two types of latex used in this study, namely concentrated latex which have dry rubber content (DRC) and depolimerization latex (latex which has decreased due to the molecular weight of polymer bonds break). Depolimerization latex in this study employed chemical methods with reduction-oxidation reaction (redox) with hydrogen peroxide (H2O2) as an oxidant and sodium hypochlorite (NaClO) as a reductant. In general, asphalt modification which has produced fulfill the quality requirements or quality standards for asphalt polymer at the value of penetration and softening point. Quality standard of penetration value is 50-75 dmm, whereas minimum value for softening point is 54oC. Modification of asphalt penetration values ranged from 49.33 to 61.25 dmm. There are two types of asphalt modifications outside the standard value, namely the modification of asphalt with a penetration of 49.52 and 49.33. Softening point value of asphalt modification ranged from 56.11oC to 65.27oC. The best asphalt modification was L5K5 sample (depolimerization latex with 5% additional doses of rubber in asphalt). Selection of the best asphalt modification was not only determined by the suitability of the penetration value and softening point with quality standard, but also was determined by homogenity between the asphalt dan rubber.
Keyword: 

Judul: Quantum Convolutional Neural Network (QCNN) for Classification Brain Tumor MRI Image
Abstrak: Penelitian ini bertujuan untuk mengembangkan model deteksi tumor otak menggunakan citra MRI dengan metode Quantum Convolutional Neural Network. Data yang digunakan adalah citra MRI otak yang terdiri dari citra tumor otak glioma, meningioma, hipofisis, dan negatif tumor yang dibagi kedalam data latih dan uji dengan rasio 80:20. Selanjutnya data latih dilakukan penyeimbangan dengan teknik oversampling. Dilakukan pengembangan model untuk mendeteksi tumor otak (biner), dan juga model untuk mengklasifikasikan jenis tumor otak (multiclass). Parameter yang digunakan dalam pengembangan model adalah jumlah ukuran filer = 2 dan kedalaman = 4, dengan qubit 4, dan dilatih dengan jumlah epoch sebanyak 10. Data akan diproses dengan metode Quantum Convolutional Neural Network yang terdiri dari lapisan quantum convolution, lapisan flatten, dan lapisan dense. Model multiclass mendapatkan akurasi 52%, setelah data latih diseimbangkan akurasi model meningkat menjadi 62%, sedangkan model biner mendapatkan akurasi 88%, setelah data latih diseimbangkan akurasi model meningkat menjadi 89%.
Keyword: Citra MRI, Klasifikasi Citra, QCNN, Tumor Otak