Judul: Daya Inhibisi Ekstrak Rimpang Jahe Merah dan Kulit Kayu Manis terhadap Aktivitas Enzim Siklooksigenase 2 dan Enzim Xantin Oksidase Secara In Vitro
Abstrak: Red ginger and cinnamon are medicine plants which can be used as anti-inflammation and lowering uric acid level in blood. In this study, water and ethanol extracts of red ginger root and cinnamon bark have been assayed for phytochemical constituent, toxicity by brine shrimp lethality test, and in vitro inhibition of cyclooxygenase 2 and xanthine oxidase activities. Diclofenac, ibuprofen and allopurinol were used as positive control. Based on phytochemical assay, water and ethanol extracts of red ginger root contained alkaloids, steroids, and flavonoids, while its water extract of cinnamon bark contained kaloids, triterpenoids, saponins, flavonoids, and tannins. The result of probit analyses of water and ethanol extracts of red ginger root and cinnamon bark showed that their LC50 values were 144 ppm, 108 ppm, 125 ppm, and 107 ppm, respectively. Ethanol extract of red ginger root showed very low inhibitory effect to cyclooxygenase 2 activity (23.81%) as compared to diclofenac (95,43%) and ibuprofen (93,59%). Water and ethanol extracts of cinnamon bark that have inhibitory effect more than 50% to xanthine oxidase were, 54.64% and 56.80%, with their IC50 values of 70 ppm and 63 ppm, respectively. Allopurinol exhibited the highest inhibitory effect (97.91%). The value of inhibitory effect showed that ethanol extract of red ginger root have low potential as inhibitor to cyclooxygenase 2 and rheumatoid drugs; water and ethanol extracts of cinnamon bark can be considered as potential as inhibitor of xanthine oxidase and can be used for uric acid drugs.
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Judul: α-Glucosidase Inhibition Activity and DPPH Free Radical Scavenging from Stratified Aqueous Extract of Red Ginger (Zingiber officinale Roxb. var Rubrum)
Abstrak: Jahe merah (Zingiber officinale Roxb. var. Rubrum) mengandung senyawa fenolik yang berpotensi menurunkan kadar glukosa darah (antihiperglikemik) pada pasien diabetes melitus. Penelitian ini bertujuan menentukan aktivitas inhibisi α-glukosidase, aktivitas antioksidan dalam meredam radikal bebas DPPH, dan kadar total fenolik ekstrak air jahe merah bertingkat (ekstrak ke-1, ekstrak residu ke-1, dan ekstrak residu ke-2). Metode penelitian yaitu ekstraksi jahe merah secara infundasi serta analisis dengan teknik uji spektronanometer yang meliputi analisis antidiabetes melalui aktivitas inhibisi α-glukosidase, aktivitas antioksidan metode DPPH, dan kadar total fenolik metode Folin-Ciocalteu. Aktivitas inhibisi α-glukosidase dan kadar total fenolik memiliki perbedaan nilai yang signifikan (p<0.05) dengan nilai tertinggi 97.729% (ekstrak ke-1) dan 27.624 mg GAE/g ekstrak (ekstrak residu ke-2). Aktivitas antioksidan dalam meredam radikal bebas DPPH memiliki perbedaan nilai yang tidak signifikan dengan nilai tertinggi 4.682 mg AAE/g ekstrak (ekstrak residu ke-1). Hasil analisis menunjukkan nilai aktivitas inhibisi α-glukosidase dan kadar fenolik total berbeda signifikan (p<0,05) dengan nilai tertinggi 97.729% (ekstrak ke-1) dan 27.624 mg GAE/g ekstrak (ekstrak residu ke-2). Hasil aktivitas antioksidan memiliki nilai yang tidak berbeda nyata (p>0,05) dengan nilai tertinggi 4.682 mg AAE/g ekstrak (ekstrak residu ke-1)., Red ginger (Zingiber officinale Roxb. var. Rubrum) contains phenolic compounds that have potential to reduce blood glucose levels (antihyperglycemic) in patients with diabetes mellitus. This study aimed to determine the inhibitory activity toward α-glucosidase, antioxidant activity in reducing DPPH free radicals, and total phenolic content from stratified aqueous extract of red ginger (1st extract, 1st residue extract, and 2nd residue extract). The red ginger was extracted by infundation and analyzed by spectronanometer test techniques which included analysis of antidiabetic through inhibitory activity of α-glucosidase, antioxidant activity using the DPPH method, and total phenolic content using the Folin-Ciocalteu method. The results of the analysis showed that the inhibitory activity of α-glucosidase and total phenolic content were significantly different (p<0.05) with the highest values 97.729% (1st extract) and 27.624 mg GAE/g extract (2nd residue extract). The result of antioxidant activity was not significantly different (p>0.05) with the highest value 4.682 mg AAE/g extract (1st residue extract).
Keyword: α-Glucosidase, Antioxidant, Diabetes Mellitus, Red Ginger

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