Judul: Desain dan implementasi komputasi paralel dengan algoritma genetik untuk prapemrosesan probabilistic neural network
Abstrak: Probabilistic Neural Network (disingkat PNN) merupakan salah satu jaringan saraf tiruan yang banyak dikembangkan bagi kepentingan manusia. PNN memiliki tingkat akurasi klasifikasi yang cukup tinggi dan waktu pelatihan yang cukup singkat. Salah satu faktor yang mempengaruhi akurasi klasifikasi PNN adalah parameter penghalus (o). Proses pencarian nilai o yang optimum merupakan salah satu prapemrosesan yang harus dilakukan sebelum masuk ke PNN. Nilai parameter o tidak dapat ditentukan secara langsung. Oleh sebab itu algoritma genetik dapat digunakan untuk mencari nilai o yang optimum. Pada umumnya solusi dari algoritma genetik semakin baik apabila jumlah populasi yang dibangkitkan cukup besar dan proses alamiah evolusi sering terjadi. Hal ini tentunya membutuhkan banyak iterasi dan sumberdaya komputasi yang cukup besar. Permasalahan ini dapat diatasi dengan menggunakan komputasi paralel yang menerapkan metode pelemparan pesan. Dengan mengkombinasikan metode algoritma genetik dan pemrosesan paralel untuk menduga parameter penghalus (σ), maka diharapkan akan diperoleh model PNN yang optimum. Penelitian ini bertujuan untuk menguji dan membandingkan kinerja dari algoritma genetik sekuensial, algoritma genetik paralel mode vektor baris, dan algoritma genetik mode vektor kolom. Penelitian menggunakan basis data bunga iris yang dikembangkan oleh R.A. Fisher. Berbagai kriteria yang digunakan untuk uji analisis adalah akurasi klasifikasi PNN, waktu eksekusi total, rasio kebergantungan mesin, peningkatan kecepatan, dan efisiensi. ...
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Judul: Optimasi jaringan syaraf tiruan menggunakan algoritme genetika
Abstrak: Neural network is one of common computational model to recognize pattern. Backpropagation algorithm can be used as method to train the networks weights. One of the drawbacks of backpropagation training is the initial weights generated randomly. It causes the instability of neural network training performance. Because of this, many experiment and training must be conducted to obtain the desired model. This research combine genetic algorithm and neural network to overcome random generation problem. Genetic Algorithm (GA) is used to find the optimal initial weights based on learning using Mean Square Error as objective function. The initial weights using GA is expected to be stable and better than those generated. The experimental research showed that genetic algorithm can be used to optimize the performance of backpropagation neural network. The optimal initial weights from genetic algorithm is more stable than the initial weights from regular method. The classification accuracy of genetic algortihm and neural network is also higher than regular method. This indicated GA method is promising to increase the neural network performance and can be applied in various real problem.
Keyword: neural network, genetic algorithm, optimation, backpropagation, classification

Judul: Development of Antioxidant Film from Basil Seed (Ocimum citriodourum) Mucilage Incorporated with Thyme Essential Oil.
Abstrak: The objectives of this research was to evaluate the effects of thyme essential oil addition on physical properties and antioxidant activity of lemon basil seed mucilage film. Lemon basil is a common name for the culinary herb (Ocimum citriodourum). This research project investigated the properties of an edible film based on lemon basil seed mucilage (LBSM) incorporated with thyme essential oil (TEO). LBSM (0.4% w/v) films were prepared by adding glycerol as plasticizers at the concentration of 30% w/w based on the weight of LBSM and then incorporated with TEO for antioxidant properties. LBSM films were given different concentrations of TEO (0%, 1%, 2% and 3% v/v) (0% as the control). The result showed that films with 3 % TEO had the highest water vapor permeability (WVP) (3.27±0.38 x10-4g mm/m2d kPa), while the control film showed the lowest WVP (1.36±0.28 x10-4g mm/m2d kPa). Water solubility were decreased with the increase in TEO concentration (p<0.05). 1% TEO films showed the highest tensile strength (5.17±0.54MPa) but lower % elongation at break (11.28±1.86%) compared to the other two films (p<0.05) (excluding the control). Scanning electron microscopy showed that the microstructure of the TEO LBSM films had a critical effect on its physical properties, further supporting the tensile strength and WVP results. The 3% TEO film exhibited the highest radical scavenging activity on DPPH (3.3±0.04 % inhibition) (p<0.05) while the others were very low and had slight difference. Increasing the amount of TEO will increase the antioxidant activity, but further increasing the concentration of TEO will also weaken the physical properties of the film.
Keyword: Lemon basil seed mucilage, edible film, antioxidant, thyme essential oil, film properties