Judul: Application of LVQ using K-means initializations for guitar tone chord recognition with MFCC feature extraction
Abstrak: Manusia dapat mengenali suara melalui proses yang dilakukan secara berulang-ulang. Namun, tidak banyak orang yang mampu mengenali suara chord gitar. Penelitian ini bertujuan untuk membuat suatu sistem pengenalan chord gitar menggunakan metode LVQ sebagai pengenalan pola dan MFCC sebagai ekstraksi ciri. Bobot awal yang digunakan pada metode LVQ diperoleh dengan menginisialisasi K-means. Data yang digunakan sebanyak 8640 data suara gitar dengan 24 jumlah chord. Masing-masing data terdiri atas 2 chord yang akan diuji secara terpisah. Parameter LVQ yang digunakan adalah learning rate 0.002, epoh 100, dan penurunan learning rate 0.9. Parameter yang digunakan dalam proses MFCC adalah time frame, overlap, jumlah koefisien cepstral dan jumlah cluster. Hasil percobaan menunjukkan bahwa akurasi maksimum yang diperoleh adalah 83.65% pada time frame 30 ms, overlap 0.4, koefisien cepstral 26, dan jumlah cluster 100., Humans can recognize the sound through a process that is done repeatedly. However, not many people are able to identify the sound of guitar chords. This study used LVQ as pattern recognition and MFCC as feature extraction. Initial weights were initialited by K-means clustering. A collection of 8640 sound data were used with 24 guitar chords. Each data consist of two chords that were tested separately. The parameters used in the process LVQ were 0.002 learning rate, 100 epoch, and 0.9 learning rate decrease. The parameters used in the process of MFCC were the time frame, overlap, the number of cepstral coefficient and the number of clusters. The experimental results showed that the maximum accuracy of 83.65% was obtained with 30 ms time frame, 0.4 overlap, 26 cepstral coefficients, and 100 clusters.
Keyword: chord gitar, Learning Vector Quantization (LVQ), Mel Frequency Cepstral Coefficients (MFCC)

Judul: Pengenalan Chord pada Gitar dengan MFCC Sebagai Metode Ekstraksi Ciri dan Jaringan Saraf Tiruan Sebagai Metode Pengenalan Pola
Abstrak: Human hearing system is capable of identifying sounds or audio signals, especially sounds that are familiar in their daily lives. However, recognizing chord sequences played in some kind of music is not an easy task. People need big effort to train their sense of hearing so that they can recognize chords. This condition is also valid for a computer system. Finding the key and labeling the chords automatically from music are of great use for those who want to do harmonic analysis of music. This research is about to recognize chords played and recorded by a guitar instrument. There are 24 chords used in this research. MFCC was used as a feature extraction using 13 and 26 cepstral coefficients. Each chord signal which has been extracted is modeled using artificial neural networks as a method of pattern recognition. This research results in an accuracy level above 90%. From the research that has been done, it can be concluded that modeling using back propagation neural networks on guitar chords recognition has an accuracy of 92%, better than the codebook method performed in the previous research which resulted in an accuracy of 88%. An increasing accuracy level is shown by using artificial neural networks for pattern recognition
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Judul: Pengembangan Bionanokomposit Film Berbasis Tapioka/Nanopartikel Perak dan Tapioka/Nanopartikel Seng Oksida dengan Plasticizer Gliserol.
Abstrak: Cassava starch can be formed into bioplastic film which is transparance as synthetic plastic films. However, pure cassava starch film has some drawbacks such as brittle, poor barrier to water vapour, sensitive to humidity and not stable during the application. The addition of nanoparticles in film was intended to increase the elongation and tensile strength, moisture stability and to provide antimicrobial activity. Meanwhile, the addition of glycerol was intended to increase the plasticity of films so they will not be easily cracked. The main purpose of this research is to elaborate the functional packaging characteristics of bionanocomposites films made from cassava starch with or without silver nanoparticles (Ag-Np) of zinc oxide nanoparticles (ZnO-Np) with glycerol as plasticizer. The addition of nanoparticles was conducted at the amount of 0%, 0,5%, and 1% by weight of the starch, whereas glycerol was used at the amount of 0% and 20% by weight of the solids (starch only or starch+nanoparticles). The value of water vapor transmission decreased significantly with the addition of Ag-Np and ZnO-Np at the concentration of 1% (from 18,0569 g/hm2 to 12,0574 g/hm2) so it enhance the water barrier of the films as packaging materials. The addition of Ag-Np and ZnO-Np at the amount of 1% with 20% of glycerol was also able to inreased the value of elongation (from 1,2% to 88,8%), but decreased the value of tensile strength (from 22,93 MPa to 4,03 MPa). The addition of glycerol gave contrary effect to the tensile strength because it produces low tensile strength values. Moreover, the results show that films made with ZnO-Np had a stronger antimicrobial activity than those made with Ag-Np for both gram positive and gram negative bacteria. In overall, it seems that the formulation of 1% ZnO-Np is the best formulation for developing bionanocomposite film based on cassava starch.
Keyword: Bionanocomposite Films, Silver Nanoparticle (Ag-Np), Zinc Oxide Nanoparticle (ZnO-Np), Cassava Starch, Antibacterial Films