Judul: Pengaruh Pemberian Tiroksin pada Waktu yang Berbeda Melalui Media Pemeliharaan terhadap Pertumbuhan dan Kelangsungan Hidup Larva Ikan Betutu, Oxyeleotris marmorata (Blkr.)
Abstrak: Percobaan ini bertujuan untuk mengetahui pengaruh tiroksin yang diberikan melalui media dengan waktu awal pemberian yang berbeda terhadap pertumbuhan sampai hari ke-9 masa pemeliharaan dan kelangsungan hidup larva ikan betutu Oxyeleotris marmorata ( 1 . ) , selama 15 h a r i masa pemeliharaan Diamati pula isi lambung dan perkembangan larva ikan betutu yang meliputi penyerapan kuning butir minyak, perkembangan sirip serta pigmentasi. rcobaan berlangsung dari tanggal 19 Juli sampai tanggal Agustus 19 9 2.
Keyword: 

Judul: Kelangsungan hidup, perkembangan dan pertumbuhan larva ikan Betutu, Oxyeleotris marmorata (Blkr.) pada penetasan dan pemeliharaan dengan media bertiroksin
Abstrak: Percobaan ini bertujuan mengetahui pengaruh hormon tiroksin yang diberikan dengan jadwal yang berbeda terhadap kelangsungan hidup, perkembangan dan pertumbuhan larva ikan betutu. Penetasan telur ikan betutu dilakukan di akuarium ka- ca ukuran 60x40x28 cm dan diberi garam natrium L-tiroksin 0.1 ppm pada hari ke-0 dan hari ke-2. Setelah berumur 2 hari larva ditebar dalam wadah pemeliharaan. Larva ikan betutu dipelihara dalam 9 buah wadah plastik volume 60 liter dan diisi air 50 liter. Padat tebar 40 ekor larva per liter. Larva diberi pakan alami (rotifera) dan pakan buatan. Pakan alami dipertahankan jumlahnya sebanyak 75 ekor per ml atau 3.75 juta per wadah setiap hari. Pakan buatan diberikan 0.5 mg per wadah per sekali pemberian dan diberi tiga kali sehari. Pakan alami dikultur dalam 4 unit bak beton secara bergilir dengan menggunakan media pupuk kotoran ayam.
Keyword: 

Judul: Application of Mel Frequency Cepstrum Coefficients (MFCC) as Feature Extraction on Phoneme Recognition with Probabilistic Neural Network (PNN) as Classifier
Abstrak: Voice recognition (speech recognition) is one field of study in voice processing. This technology can convert voice signals into a form of written information (text). With this technology, people can interact with a computer. MFCC feature extraction computes the cepstral coefficients by considering the human hearing. This research is a phoneme recognition using feature extraction MFCC and PNN as feature matching model. This study compares the coefficient, overlap, and the test data without noise and with noise. MFCC is used with 13, 20, 26 coefficients and 0%, 25%, 50% overlap. Noise is added by 30 dB, 20 dB and 10 dB. From the comparison of the three overlaps, produced the best accuracy at 50% overlap with an accuracy of 94,71%. From comparing the three coefficients, better accuracy resulting in coefficients of 20 and 26 with an accuracy of 97,12% at 50% overlap. After comparing between the coefficients of 20 and 26 with overlap of 25% then the coefficient 26 is obtained that better accuracy of 94,23%. This shows that in this study the coefficient 26 is the best. In this research, there are three noise variables. The variables are 10 dB, 20 dB, and 30 dB. The best accuracy reached when the noise variable is 30 dB rather than 10 dB or 20 dB because the accuracy has the closest accuracy compared by the accuracy when noise was not added into the data. When the noise variable is 30 dB, the percentage of accuracy is 85,3%.
Keyword: