Judul: Friesian Holstein Bull Frozen Semen Quality Using Skim Milk and Citrate-Egg Yolk Nanoparticles Extenders
Abstrak: Inseminasi buatan menggunakan semen beku dilakukan untuk meningkatkan populasi sapi Friesian Holstein (FH) di Indonesia. Penelitian ini bertujuan membandingkan kualitas semen beku sapi FH menggunakan pengencer susu skim dan sitrat-kuning telur nanopartikel. Kuning telur nanopartikel dibuat dengan metode milling selama 110 menit. Semen dikoleksi menggunakan vagina buatan, kemudian dievaluasi dan diencerkan dengan pengencer Susu skim (SK), Sitrat kuning telur nanopartikel 5% (SKTN 5), Sitrat-kuning telur nanopartikel 10% (SKTN 10), dan Sitrat-kuning telur nanopartikel 20% (SKTN 20. Semen diekuilibrasi, dibekukan dengan uap nitrogen (N2) cair, direndam sesaat dalam N2 cair dan disimpan dalam kontainer N2 cair. Semen beku dithawing dengan air hangat (37ºC) selama 30 detik dan dievaluasi kualitasnya terhadap karakteristik motilitas progresif, dengan metode estimasi dan CASA, viabilitas, membran plasma utuh (MPU), dan recovery rate (RR). Perbedaan nyata (P<0,05) ditemukan pada motilitas porgresif, MPU, dan RR dari spermatozoa. Pengencer Sitrat-kuning telur nanopartikel secara keseluruhan mampu mempertahankan kualitas spermatozoa selama proses pembekuan lebih baik jika dibandingkan Susu skim., Artificial insemination using frozen semen is used to increase the population of Friesian Holstein (FH) cattle in Indonesia. This study aims to compare FH frozen semen quality using skim milk and egg yolk nanoparticle-citrate extenders. To make nanoparticles, egg yolks were milled for 110 minutes. The semen is collected using artificial vagina, then evaluated and diluted with Skim milk (SM), Egg yolk nanoparticle-citrate 5% (EYNC 5), Egg yolk nanoparticle-citrate 10% (EYNC 10), and Egg yolk nanoparticle-citrate 20% (EYNC 20). Semen is then equilibrated, frozen by liquid nitrogen vapor, and then submerged in liquid nitrogen before stored in liquid nitrogen. The frozen semen is thawed with warm water (37ºC) for 30 seconds and then evaluated. The quality of frozen semen was evaluated by the progressive motility, using estimation and CASA method, viability, membrane integrity (MI), and recovery rate (RR). Significant differences (P<0.05) were found among the sperm progressive motility, MI, and RR. Egg yolk nanoparticles in citrate buffer can maintain sperm quality in cryopreservation better than skim milk
Keyword: CASA, egg yolk nanoparticle, Friesian Holstein, frozen semen, skim milk

Judul: Longivitas dan Viabilitas Spermatozoa Sapi Friesian Holstein, Simmental, dan Brahman dalam Semen Beku Menggunakan Pengencer Skim.
Abstrak: Indonesia had two artificial insemination centre and more than 17 regional artificial insemination centre. Before distributed to farmers, the quality of frozen semen has to be laboratory tested periodically. According to the Indonesian National Standard the parameters assessed in the laboratory are sperm motility and individual scoring. The aim of this study was to test the sperm motility, viability and longevity of frozen semen from three cow breeds which are FH, Simmental and Brahman produced by one of the regional artificial insemination centers and to fine out the relationship between sperm motility and its viability among breed. Results showed that post thawing motility of the FH bull was 50.00±0.00% which was significantly higher than Simmental 43.50±2.42% or Brahman 43.33±2.50% bull. A decrease in motility and viability showed an association motility with the percentage of live spermatozoa. They were no differences in sperm longevity among breeds. The motility of all samples decreased and reached 0% motility in 5 hours. The decrease in sperm motility and viability is caused by the decrease in energy sources and the accumulation of toxic waste of metabolized diluents. In conclusion, the FH bull had the best post thawing motility and viability compared to Simmental and Brahman bull. Based on the Indonesian National Standard all sample could be used for insemination.
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Judul: Pengembangan Model Codebook untuk Identifikasi Chord Gitar
Abstrak: Acoustic guitar can produce sound waves with different types of tones. High-low tone is determined by the fundamental frequency of the sound wave. Human sense of hearing can distinguish high-and low tones, but can not know for sure what kind of tone is heard by him. This study developed a guitar chord recognition system. This study uses MFCC as feature extraction methods and the codebook as pattern recognition method for identification of the guitar chord. Cluster technique used in this study is the K-means clustering. Data obtained from MFCC are clustered using the K-Means method, and the model for classification is constructed using the codebook method. The parameters used in MFCC is the number of cepstral coefficients, overlap, and the time frame, while an important parameter in the K-Means is the number of clusters. This study uses 8640 guitar chord sounds from 24 classes. Each of the data is made up of two chords which will be tested. Simulation results show that the maximum accuracy obtained is 98.89% obtained on 26 cepstral coefficients, overlap 0.4, time frame is 30 ms, on 100 clusters.
Keyword: chord, codebook, k-means, mel frequency cepstral coefficients (MFCC)