Judul: Pengenalan Pembicara Dengan Mel Frequency Cepstrum Coefficient (MFCC)     Sebagai Metode Ekstraksi Ciri Dan Jaringan Saraf Tiruan Propagasi Balik Sebagai     Metode Pengenalan Pola
Abstrak: Suara yang dimiliki setiap manusia mempunyai ciri khas tersendiri yang dapat dijadikan sebagai alat identifikasi. Identifikasi pembicara atau speaker recognition merupakan salah satu aplikasi dalam ranah Natural Language Processing yang merupakan suatu sistem untuk mengidentifikasi siapa yang berbicara. Penelitian dilakukan dengan merekam suara beberapa orang. Kemudian suara diolah dengan tahapan silence Elimination, dilanjutkan dengan ekstraksi ciri dengan metode Mel Frekuensi Cepstrum Coefisien (MFCC). Pemodelan menggunakan Back Propagation Neural Networks sebagai metode pengenalan pola. Dari penelitian yang telah dilakukan dapat disimpulkan bahwa Pemodelan penggunaan Back Propagation Neural Networks pada pengenalan speaker mempunyai akurasi sebesar 94,02% lebih baik dibandingkan dengan penggunaan Resilient Backpropagation sebesar 92,8% pada penelitian sebelumnya. Akurasi terbaik Back Propagation Neural Networks dengan 50 lapisan tersembunyi, perbandingan data test dan data train 60:40, dan overlap 40%. Pengujian dengan penambahan noise 30dB pada pengujian data akurasi meannya adalah 92,27%, noise 20dB pada data dengan akurasi rata-rata 73,55%, noise 10dB pada data dengan akurasi rata-rata 24% dan pada data dengan noise Akurasi rata-rata 5dB adalah 13,31%.
Keyword: Backpropagation ANN, back propagation ANN, MFCC, Speaker Recognition

Judul: Speaker Identification System Modeling Using MFCC as Feature Extraction and SVM as Pattern Recognition
Abstrak: Everyday people exchange information using voice may also exchange information with the media texts and tools. Voice signal every human has the character and qualities of different or unique. Indonesia has a diverse ethnic, communities and cultures, many problems are for the same word has different pronunciation patterns. Because of this problem could be a problem in the speaker identification system, so it is necessary to develop a system that is relatively more robust to the problem of intra-speaker variability and noise. Speaker identification system is more focused on the analysis of the two subsystems, namely Feature Extractor and Pattern Recogniser. Mel-Frequency Cepstrum Coefficients (MFCC) is one of feature extraction that is often used for processing the human voice for calculating the cepstral coefficients with the consideration of human hearing. Support Vector Machine (SVM) is one of the classification techniques of data with the supervised learning that is able to classify the multi-class so it is suitable for the classification of more than two classes. Data collection was performed using a microphone to record sound. Sound source was obtained from 10 adult speakers with differences in gender, age and ethnicity, which each speakers say 50 times the word "COMPUTER" so that obtained 500 data. Record duration is 2 seconds with a frequency of 16 KHz. Before data is processed, a preprocessing stage consisting of the elimination of silence, normalization and noise addition. Gaussian noise is added from the level of 80 dB to 0 dB. After the MFCC feature extraction is done, the next stage is SVM pattern recognition using QP and SMO algorithms. Kernel function tested for RBF, Linear, and Quadratic for each algorithm. Pattern Recognition using Kernel quadratic function with a ratio of 90 : 10 for the test data that the original sound without noise, SMO algorithm produces accuracy of 97.0% and the accuracy of the system can maintain above 70% up to 40dB noise addition. The number of errors for all 10 speakers using the test data of the original sound without noise is at most the number 9 speakers (Male, 41 years old, Java). The processing time SMO algorithm is better than the QP algorithm. Future studies may be added to increase the accuracy of Noise Cancelling the voice data is contaminated by noise.
Keyword: Speaker Identification, MFCC, SVM

Judul: Mercury Toxicity and It’s Effect on Histopathology Change of Nile Tilapia (Oreochromis niloticus).
Abstrak: Nile tilapia (Oreochromis niloticus) is one of fish species that oportunity to contaminated with mercury. The effects of pollutants can damage living organisms organs and can cause death. The effects caused mercury had acute or chronic character. The aims of this study are to determine threshold and acute toxicity of mercury chloride (HgCl2) of Nile tilapia (Oreochromis niloticus), to assess the effect of mercury chloride (HgCl2) on several biometric parameters (survival, growth rate of average daily weighted, liver condition, bile and reproductive variability of Nile tilapia (Oreochromis niloticus), assess the level of damage to the histological structure of the gills, liver and kidney of Nile tilapia (Oreochromis niloticus) caused mercury chloride (HgCl2) exposure. This study was conducted from February to June 2013. Nile Tilapia (Oreochromis niloticus) were used in this study were female with average weight 20 grams or 11-13 cm length range. Toxicant materials used in this study was mercury chloride (HgCl2). Fish were reared in each aquarium 60x40x30 containing 48 liters of water. This study consists of three stages: a preliminary test, acute test, and sub-chronic test. To determine the changes in biometric condition of tilapia approximated by measuring the survival rate (SR), the growth rate of average daily weight , the content of mercury in the fish organs, hepatosomatic index (HSI), the relative bile volume (VER), gonadal soamtic index (IKG), fecundity and oocit diameter, tissue damage caused by mercury in fish organs by making histological preparations stained with hematoxylin and eosin. The median lethal concentration (96 hr, LC50) of Mercury Chloride was calculated as 1,64 mgL--1.The survival rate was highest in the control treatment (46,67 %) . Mercury chloride with concentration 0.196 mgL--1 show significant effect to changes HSI and relative bile volume, and oocyte diameter of Nile tilapia (p < 0,05). Mercury chloride with a concentration of 0,164 mgL-1 and 0,196 mgL-1 have not a significant effect on the growth rate of weight, gonadal somatic index and fecundity of Nile tilapia (p > 0,05). Mercury chloride cause damage to gills (hyperplasia, hypertrophy, proliferation and neukrosis), liver (hyperplasia, hemorhage, shrinkage of hepatocytes, proliferation and neukrosis) and kidney (hyperplasia, hemorrhage, shrinkage of the glomerulus, proliferation and neukrosis).
Keyword: Nile tilapia, Hepatosomatic indexs (HSI), histopathology