Judul: Pembangunan Metode Codebook untuk Identifikasi Chord Gitar dengan Teknik Ekstraksi Ciri MFCC
Abstrak: Various types of chords can be produced by a guitar instrument. However, it is difficult to recognize a guitar chord manually. This research develops a system to recognize a chord on the guitar using codebook, MFCC, and K-means clustering. The codebook is used as the pattern recognition method for identification of guitar sound, while MFCC is used as a method of feature extraction. The parameters used in the process of MFCC are the number of cepstral coefficients, overlap, and the time frame, while the parameter used in the process of K-means clustering is the number of cluster. This research used 1440 guitar sound data that are divided into 72 class, so that each class has 20 guitar sound data. The results showed that the maximum accuracy obtained is 99.72% when the number of cepstral coefficients are 26, overlap value is 0.4, time frame is 30 ms, and the number of cluster is 5.
Keyword: Chord, Codebook, Guitar, K-Means, MFCC

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)

Judul: Peranan Infeksi Transplasental Virus Bovine Viral Diarrhea Pada Sapi
Abstrak: Tulisan ini bertujuan untuk mengetahui peranan infeksi transplasental virus bovine viral diarrhea pada sapi ditinjau dari segi patogenesa dan imunitasnya. Bovine Viral Diarrhea (BVD) merupakan penyakit pada saluran pencernaan dan pernafasan yang ditandai dengan gejala demam, salivasi, keluarnya sekresi nasal dan kadang-kadang diikuti diare. Penyakit ini disebabkan oleh Pestivirus. Penularan penyakit BVD pada sapi dapat terjadi melalui kontak secara langsung maupun tak langsung dengan sekresi dan ekskresi yang dihasilkan sapi yang terinfeksi virus BVD. Domba, rusa dan babi dapat pula menularkan penyakit ini pada sapi. Pada sapi tidak bunting, infeksi ini menyebabkan penyakit pada saluran pencernaan dan pernafasan yang bersifat ringan. Sapi yang terinfeksi virus BVD akan segera membentuk zat kebal dalam tubuhnya. Kekebalan yang telah terbentuk dapat melindungi sapi tersebut terhadap infeksi virus BVD selanjutnya. Sedangkan pada sapi bunting, infeksi ini selain menyebabkan penyakit pada saluran pencernaan dan pernafasan juga dapat mempengaruhi perkembangan fetus melalui infeksi secara transplasental.
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