Judul: Mikroenkapsulasi Ekstrak Rimpang Temulawak (Curcuma xanthorriza. Roxb) Tersalut Gel Kitosan-Alginat
Abstrak: Microencapsulation was done using the temulawak extract with curcumin as a target material. The aims of this research were to study (1) the transport properties of curcumin passing through the chitosan-alginate membranes due to diffusion process, (2) the optimum condition of in vitro dissolution behavior, and (3) the effects of oxidation and hydrolysis to storage conditions of curcumin coated chitosan-alginate gel. The maceration process using ethanol yields 17.08% and the content of the curcumin in the extract detected by visible spectrophotometry λ 430 nm was 10.30%. Chitosan-alginate membranes were prepared by mixing 100 ml chitosan 2.50% (b/v); 16.7 ml alginate 0.62% (b/v); and 1.70 ml glutaraldehide 4.63% (v/v) solutions, were poured into mould. Membranes thickness was varied by changing chitosan solution volume. Then, the membranes were used in diffusion assay at 37 and 40oC. Two degrees of donor concentration (Cd) was used 4 and 8 g/l, whereas recipient compartment was filled with solvent. Aliquots were taken after 30, 60, 90, 120, 150, and 180 minutes. The Aliquots absorbance was measured at λ 430 nm. Based on linear regression method, it was found that the influence of T, Cd, and h on D, J (Fick), and D, Jo (Higuchi), were not significant. On the other hand, the influence of T, Cd, and h on D, J (Fick), and D, Jo (Higuchi) using response surface method yield model equations with R2 98.6% and 99.4%. Matrix formation of curcumin for sustained released which is coated by chitosan-alginate gel ware made in a form of a microencapsulation using spray dryer technique. Its optimum condition was obtained using response surface method at concentrations ratio of alginate 0.62% (b/v) and glutaraldehide 4.63% (v/v) respectively, while chitosan concentration was fixed (1.75% [b/v]). The dissolution assay was done at 37oC, at 100 rpm of stirring rate in 8 hours. Aliquots were taken at 15, 30, 45, 60, 90, 120, 150, 180, 240, 300, 360, 420, 480 minutes. Absorbance of the Aliquots was measured at λ 430 nm. The curcumin released has the best linear correlation to the first order reaction with released constant, k = 2.25.10-3 minute-1 while it’s half live is t1/2= 5.16 hours. Release curcumin was determined mainly by diffusion mechanism. The Higuchi model was better than Fick model for determined the dissolution process. The storage assay for the microencapsulation process of temulawak ethanol extract showed that the room temperature was the best condition for maintaining the curcumin release. In this case, the data was suitable with the third order reaction with released constant, k = 0.6193 10-3 week-1 while it’s half life was t1/2 = 29.90 week.
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Judul: Perilaku Disolusi Mikrokapsul Ketoprofen Tersalut Gel Kitosan-Alginat Berdasarkan Ragam Konsentrasi Tween 80
Abstrak: Chitosan ability to form gel has been extensively studied and modified; natural hydrocoloid addition is just an example. Chitosan-alginate gel has a promising potential to be applied as a good coating material in drugs delivery system. In this study, chitosanalginate gel coated ketoprofen microcapsules were made using spray drying method. Tween 80 solution concentration used in the process was varied (1, 2, and 3% (v/v)). The resulting microcapsules particle sizes were ranging from 150 nm to 6 μm. The dissolution test results showed that the Tween 80 solution concentrations were affecting ketoprofen releasing rate for the microcapsule. Maximum ketoprofen release rates either in acidic or basic medium were observed at 2% Tween 80 concentration. The maximum released ketoprofen amounts in acidic and basic medium were 35.19 and 287.92 ppm, respectively. The releasing mechanism was determined by evaluating the releasing kinetic models. The ketoprofen releasing kinetic model, both in acidic and basic medium, was following the Hixson-Crowell kinetic model.
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Judul: Pengembangan model probabilistic neural network (PNN) pada pengenalan kisaran usia dan jenis kelamin berbasis suara
Abstrak: Voice signal can be used to represent a speaker. Voice can also be used to recognize the age range and the gender of the speaker, because of the difference in frequency of the voice signal for different age and gender. Age range for this experiment is divided into children (8-10 years old), teenagers (12-17 years old) and adults (30-50 years old). We performed feature extraction to obtain a representation of the speaker using Mel-Frequency Cepstrum Coefficient (MFCC). MFCC is used with 13, 20, 26 coefficients. Probabilistic Neural Network (PNN) is used as the feature matching model. The PNN model is constructed from three different proportions of TRD (Training data) : TSD (Testing data) (25%:75%, 50%:50%, 75%:25%). MFCC with 26 coefficient gives the best accuracy of 93.47%. The proportion of 75% (TRD) : 25% (TSD) also gives the best accuracy of 94.22%. PNN-age and PNN-gender identification result in an accuracy of 91.26%. Specifically, PNN accuracy percentage for male and female are 92.26%, and 95.20%, respectively, while for children, teenagers and adults the accuracies are 99.85%, 92.28% and 95.57%, respectively. In conclusion, the average of accuracy for all categories is 91.26%. The experiment using the voice of male-teenagers gives the worst accuracy, which is caused by the overlapping frequencies of voice in children, teenagers and adults.
Keyword: Voice identification, PNN model, MFCC, Age-identification, Gender-identification