Judul: Formulasi sediaan obat kumur berbahan dasar gambir (Uncaria gambier Roxb)
Abstrak: Mouth sanitary is something that important for human, especially on daily social intercourse. On healthy human, mouth foul that happened usually originate fiom inside of mouth caused food residue decaying by bacteria which exist in mouth cavity. Some solution to contend mouth foul caused by various diseases in mouth is by using antibacterial mouthwash which can kill or obstruct the plaque maker bacteria, especially Streptococcus mutans bacteria. Gambier is rubber essence which extracted fiom gambier leaves (Uncaria gambier Roxb) by pressure method (Amos, et al, 2004). Gambier with two main components that are catechin and cathecutannic acid, has an astringent effect, antibacterial, pharmacological and other toxic properties. But the exploration of gambier advantages still not optimal. Gambier uses as a mouthwash preparation is one of the efforts in gambier advantages exploration. Additionally, gambier mouthwash will be able to replace the commercial mouthwash which usually contain high enough of alcohol. Mouthwashes with alcoliol content of 25% or more have been implicated in mouth, tongue and throat cancers about 50% (Brooking and Zaman, 2005).
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Judul: Formulasi Obat Kumur Gambir (Uncaria gambir Roxb)
Abstrak: Gambier (UI/CClria gambir Roxb) is rubber essence which extracted from gambier leaves by pressure method (Amos et aI., 2004). Gambier with two main component that is catechin and catechutannic acid, have an astringent effect, antibacterial, pharmachological properties, and other toxics. That properties makes gambier often used medicine and pharmacy industry, leather tanning industry, and others. Though gambier have a lot of uselfulness, the exploration of gambier advantages still not optimal yet. Use gambier to be mouthwash preparation is one of the effort in exploration of gambier advantages, Gambier mouthwash will be able to replace the commercial mouthwash which contain alcohol and others syintetic chemicals, Mouthwash with an alcohol content of 25% or more have been implicated in mouth, tongue, and throat cancers about 50% (Brooking, 2000), The aim of this research is to get the best formulation of gambier mouthwash which can be inhibit to Streptococcus J17ulans growth and accepted by consumen by organoleptic test. Analysis which conducted at gambier mouthwash cover the examination of antibacterial activity, pH, viscosity, microbiology (total microbe) and organoleptic test which includes transparency, color, aroma (odor), taste and overall. Commercial herbal mouthwash was used as comparator. This research has resulted formulation of gambier mouthwash own the pH about 6.02-6.11, while pH of comparator is equal to 6.14, Viscosity of gambier mouthwash is about 1.85-1.93 cP, while the comparator having viscosity equal to 1.34 cr. Antibacterial activity has showed by diameter of zone of iIlhibilion is equal to 34.05-34.35 ml11, control ° 111m (none zone of inhibition), while the comparator equal to 28.55 mm. Formulation of gambier mouthwash and \.nmparator own the same total microbe, that is 0 co!ony/ml. Result of the manner analysis has showed that the variation of gambier concentration has not influence the antibacterial activity and pH value, but influence the viscosity of gambier mouthwash. Result of organoleptic test which includes transparency, color, taste and overall has indicate that gambier tnol1thwash which most accepted by the consumer is formulation of gambier mouthwash with the gambier concentration 0,2%.
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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