Judul: Pengembangan Model Probabilistic Neural Network untuk Identifikasi Chord Gitar
Abstrak: Pengenalan kunci gitar membutuhkan teknik ekstraksi ciri dan model pengenalan pola. Penelitian ini membangun sistem pengenalan suara gitar menggunakan teknik MFCC sebagai pengekstraksi ciri dan PNN sebagai pengenal pola. Tujuan penelitian ini adalah menemukan parameter-parameter yang menghasilkan akurasi terbaik. Parameter-parameter tersebut terkait dengan MFCC, yaitu jumlah koefisien cepstral, overlap, dan time frame. Sistem bekerja dengan membaca file suara berformat WAV, kemudian file diproses dengan teknik MFCC dan PNN untuk menghasikan keluaran kunci suara gitar berupa teks. Penelitian ini menggunakan 8 280 data suara gitar dari 24 chord yang berbeda. Hasil penelitian menunjukan bahwa koefisien cepstral 52, overlap 0.4, dan time frame 100 ms menghasilkan akurasi maksimum yaitu 96.56%.
Keyword: identifikasi kunci gitar, mel frequency cepstral coefficients (MFCC), pengenalan suara, probabilistic neural network

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: Biology and ecology of the buffalo fly, haematobia exigua de meijere (diptera:muscidae)
Abstrak: The life history of the buffalo fly was observed at room temperature of 27°-29.5°C and at a relative humidity of 48-68 percent. The eggs hatched after 17-22 hours, with an average of 18 hours. First instar larvae measured 1.25 + 0.16 mm long and 0.27 + 0.037 mm wide. reach the second larval stage. It took 6-12 hours to the second instar larvae measured 2.676 +0.187 mm long and 0.353 +0.028 mm wide. The second instar took about 12-24 hours to reach the third larval stage. The third instar measured 6.833 + 0.189 mm long and 0.919 + 0.051 mm wide. It took about 2-3 days for the third instar to become pupae. Duration of the pupal stage was about 5-7 days before the adults emerged. Under laboratory condition, the buffalo fly completed its life cycle in 9.5 to 10.5 days, whereas under field condition it took 9-14 days with an average of 10.5 days. The growth ratio which was based on the measurements of the cephalo-pharyngeal skeleton of each instar was 1.797. The preoviposition period was 8-12 days and mating usually occurred on the 6th or 7th day. The longevity of the male was 29 days, whereas it was 32 days in the female. The range of egg production under laboratory condition was between 20-139 per female fly. The belly and hind legs of the carabao were the most preferred habitat either during cloudy and cool dry or shiny and warm day. When the weather was clear and the carabao was in the shade, the flies tended to be more distributed particularly on the shoulder, dewlap, back and horns. The carabaos had relatively fewer Musca sp. and Stomoxys calcitrans than cattle; never the less carabaos had a higher infestation of buffalo fly than cattle. Oviposition occured either during the day or night but the buffalo flies were more active during the night than in the day time. The effect of various lengths of exposure time of manure in relation to the oviposition was profound. observed, the maximum number of the buffalo flies was occurred when the dung was exposed for 30 minutes. With increasing time of exposure the number and variety of insects also increase. It was evident that Sepsidae and psychodidae were the most dominant insects emerging from the dung. The number of buffalo flies also increased with increasing
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