Judul: Sistem penunjang keputusan pendirian industri alkil poliglikosida
Abstrak: Fndonesia produced 299.447 tons of fatty alcohols in 2010. Fatty alcohol isprimary substance surfactant.Surfactant demand in 2001 was 10million tons. The development ofsurfactant requires Environmental friendly and natural-based material. APG is a surfactant synthesis form fatty alcohol and starch. APG industrial establishment is less developed due to lack of information of industry in establishment. The objective of this research is to create decision support systems (DSS) of APG dustrial establishment in Indonesia. The system consists of factors affected in development of the industry. Method in system development is the System Development Life Cycle. DSS resulted a decision, APG industrial locations in Medan, North Sumatra. Demand of APG was 415,402 tons. The Fesults of the financial feasibility with 6000 ton/years has passed proper test. Feasibility analysis of The industry re Net Present Value (NPV) of Rp 26,706,034,159.00, Internal Rate of Return (IRR) of 22.9%, Benefit Cost Ratio (B/C ratio) of 1301 and the Pay Back Period (PBP) of 5.4 years.
Keyword: Alkylpolyglicosides, Decision suport system, System development life cycle

Judul: Sintesis Surfaktan Alkil Poliglikosida dari Fatty Alcohol (C16) Sawit dan Glukosa Cair 85% dengan Perlakuan Perbedaan Nisbah Mol.
Abstrak: Surfactants (surface active agents) are the surface tension active compounds that can be produced synthetically chemically or biochemically. Surfactants are used in industry as a bleaching, wetting, foaming materials, as well as emulsifier and others. The addition of the surfactant is expected to optimize the performance of the active ingredient used. This provides opportunities to develop further research. One type of surfactant that is being developed is poliglicoside alkyl surfactants (APG). APG Surfactant is a nonionic surfactant type commonly used in the formulation of some products such as herbicide formulations, personal care products, cosmetics, textile fabric bleaching and surfactants solution for Enhanced Oil Recovery. Raw material of APG surfactant are fatty alcohol from coconut oil oleochemicals or palm kernel oil (fatty alcohol C16) and glucoside 85%. Fatty alcohol is hydrophobic (lipophilic), while glucose is hydrophilic. In this research APG surfactant was synthesized from fatty alcohol palm oil (C16) and 85% liquid glucose. The Purpose of this research is to obtain the best reactant mole ratio of surfactant alkyl Poliglicoside the best of Fatty alcohol (C16) oil with Liquid glucose 85%. This study used a completely randomized experimental design with one factor and two repetition. The treatment used was reactant mole ratio with five concentration level ie 1.5, 2, 2.5, 3 and 3.5. The process used in this research was 2-stage of processes, there are butanolisis and transacetalitations. The best formula was obtain from the ratio of 1 mol glucoside with 1.5 mol fatty alcohool. This product resulted on the lowest interfacial tension of 5.56 x 10-2 dyne/cm. This APG was processed at a temperature of 120-130OC for 2 hours.The pH value was in the range of 8.2-8.52
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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