Judul: Manipulasi Fotothermal Dalam Memacu Pematangan Gonad Ikan Senggaringan (Mystus nigriceps)
Abstrak: Fotoperiode, temperatur dan curah musim hujan adalah beberapa faktor lingkungan yang sangat penting dalam mengatur siklus reproduksi ikan. Di alam, faktor lingkungan menentukan sebagain besar pemilihan waktu reproduksi dan strategi reproduksi jenis ikan-ikan tertentu. Beberapa penelitian terhadap spesies subtropis memperlihatkan adanya dampak positif terhadap reproduksi ikan. Scott (1979) menambahkan bahwa faktor lingkungan yang dominan mempengaruhi perkembangan gonad adalah temperatur dan makanan termasuk periode pencahayaan dan musim, kemudian ditambahkan bahwa periode penyinaran yang rendah dan temperatur yang tinggi dapat mempercepat pematangan gonad.
Keyword: 

Judul: Photothermal Manipulation on Advance of Gonadal Maturation in the Senggaringan (Mystus nigriceps)
Abstrak: Photothermal has been considered one of the most important factors triggering puberty, as well as reproduction, in several fish species, including Senggaringan. Senggaringan is one of the wild fish living in the Klawing river and high economic value and in the future it is expected to become one of aquaculture commodities. As the activity of fishing has done constantly and begun to cause fish habitat damage, the fish has been rare in the market even catches by fishermen tend to decrease. To maintain the existence of this fish, there needs domestication efforts ultimately leading to conservation. This research was laboratory experiment using completely randomized factorial design to apply nine different photothermal treatments, namely: 1) natural temperature and duration of natural lighting (T0L0), 2) natural temperature and duration of lighting 10L:14D (T0L1), 3) natural temperature and duration of lighting 14L:10D (T0L2), 4) temperature of 25oC and duration of natural lighting (T1L0), 5) temperature of 25oC and duration of exposure 10L:14D (T1L1), 6) temperature of 25oC and duration of exposure 14L:10D (T1L2), 7) temperature of 30oC and duration of natural lighting (T2L0), 8) temperature of 30oC and duration of exposure 10L:14D (T2L1) and 9) temperature of 30oC and duration of exposure 14L:10D (T2L2). Results showed among the photothermal treatments tested that there were two treatments supporting the development of the fish ovary. The first, the GSI values in T0L1 treatment continuously increased until the end of the experiment from 5.7% to 15% (highest). However, statistically there was no significantly different among treatments (P>0.05, P=0.077). The results of this research also showed that an increase in GSI value of 15% (T0L1) caused to lower values for HSI 1.3% (P>0.05, P=0.061) and VSI 1.6% (P>0.05, P=0.058). The second, in T1L0 treatment, highest GSI value was achieved in August by 13.3% from 7.1%. There also occurred a decrease in HSI value of 1.2% and value VSI of 2.6%. The value of the GSI before photothermal was 3.7%. This profile showed the negative relationship between the GSI and HSI, and also negative relationship between GSI and VSI with the meaning which the increase in the GSI values declined in values of HSI and VSI. Based on the proportion of oogenesis phase cells showed that late vitellogenesis stage for the highest was achieved about 41.2% in the treatment T1L0. However, based on statistical tests there was no significant difference among the treatments (P>0.05, P=0.2). The value of final vitellogenesis before photothermal was 10.2%. Thus, it can be concluded that the gonadal development of the fish female under the photothermal manipulation has not shown maximum performance. It seems that there is needed to extent exposure of lighting to affect its gametogenesis.
Keyword: 

Judul: Klasifikasi dengan Analisis Komponen Utama Kernel
Abstrak: Principal component analysis (PCA) is a special case of the kernel PCA with linear kernel function. The aim of this study is to resolve the data problem that is not linearly separated and to classify an object into a group by using kernel PCA to obtain the smallest classification error. Group classification using kernel PCA is performed by the linear and Gaussian kernel function. The result of the study shows for wine recognition data with the linear and Gaussian (parameter 2.5) kernel function produces 30.889% and 17.416% classification error, respectively
Keyword: classification error, kernel, principal component analysis