Judul: Efektivitas ekstrak daun mahkota dewa dan daun mengkudu sebagai moluskisida nabati terhadap daya hidup keong mas (pomacea canaliculata lamarck)
Abstrak: Penggunaan moluskisida nabati dalam penanggulangan keong mas merupakan salah satu upaya untuk menekan penyebaran hama keong mas. Daun mahkota dewa dan daun mengkudu diduga dapat menjadi moluskisida nabati bagi hama keong mas karena mengandung senyawa saponin. Penelitian ini bertujuan menguji efektivitas ekstrak daun mahkota dewa dan daun mengkudu sebagai moluskisida nabati terhadap daya hidup keong mas. Sampel keong mas berasal dari daerah pesawahan di desa babakan, bogor. Keong mas yang digunakan adalah keong mas besar dengan ukuran operkulum 11 – 20 mm dan keong mas kecil dengan ukuran operkulum 5 – 10 mm. Rancangan percobaan yang digunakan adalah rancangan acak lengkap (ral) dengan analisis anova melalui program minitab 16 dan untuk menentukan lethal dosis (ld50) dianalisis dengan metode probit. Hasil penelitian menunjukkan bahwa ekstrak daun mahkota dewa dan daun mengkudu efektif menurunkan daya hidup keong mas hingga mencapai 0% pada konsentrasi 10 g/l pada waktu pemaparan 72 jam, sedangkan pada konsentrasi 25 g/l dapat menurunkan daya hidup keong mas hingga mencapai 0% pada waktu 48 jam dan 72 jam. Hasil penelitian juga menunjukkan bahwa ld50 terkecil terdapat pada daun mahkota dewa jam ke-72, yaitu 2.43 g/l. Efektivitas ekstrak daun mahkota dewa terhadap penurunan daya hidup keong mas lebih tinggi dibandingkan dengan ekstrak daun mengkudu.
Keyword: daya hidup, keong mas, mahkota dewa, mengkudu, moluskisida nabati

Judul: Efektivitas Ekstrak Daun Nangka dan Daun Sukun sebagai Moluskisida Nabati terhadap Daya Hidup Keong Mas (Pomacea canaliculata Lamarck)
Abstrak: Golden apple snails (Pomacea canaliculata Lamarck) are pests that attack water plants, especiallypaddy field until 30 days old. One effort to eradicate the snails without leaving chemicals residue in plants is by the provision of natural pesticides such as molluscicides. Jackfruit and breadfruit leaves maybe used as natural molluscicides for snail because they contain saponins. This study aims to test the jackfruit leaf and breadfruit leaf extracts to the survival of snails and determine the effectiveness of the leaf extract based on the LC50. The experiment was conducted separately for small (operculum diameter 5-10 mm) and large golden snails (operculum diameter of 11-20 cm). During the experiment the snails were put in a jars filled with water without leaf extract as the control, and jars with leaf extract at a concentration of 5 g/L, 10 g/L, and 25 g/L as treatments. Observations were carried out by counting the number of snails survives after 24, 48, and 72 hours. The results were analyzed to obtain LC50 values. Jackfruit and breadfruit leaves extracts have potential as molluscicides, since they caused all the snails died on the third day of treatment (72 hours). Decreasing rate of their survival is faster at higher concentrations. The presence of mucus in the body of the dead snails showing symptoms of the effect of saponins. Inconsistent results seem appear on LC50 (24 and 48 hours) of breadfruit extract. LC50 of 24 hours (large snails) and 48 hours (small snails) since they are not detected at the treatment using jackfruit leaves. This suggests the need to redesign the method and the concentration used for better research results.
Keyword: snails., Bogor Agricultural University (IPB), breadfruit, Pomacea canaliculata, Pomacea canaliculata, molluscicides, jackfruit

Judul: Pengenalan Wajah dengan Citra Pelatihan Tunggal Menggunakan Algoritme VFI5 Berbasis Histogram
Abstrak: Face recognition is one of the biometric methods which is frequently used. One of the approach in face recognition is view based (photometric) approach which represents the information of the image pixels. In this research, information from the image pixels represented using the image histogram. According to Gonzales (2002), histogram are the basis for numerous spatial domain processing techniques. Histogram is used as input to Voting Feature Intervals 5 (VFI5) algorithm. Range of image histogram is 0-255 divided into several intervals. Afterwards, on training stage will be determined the vote value from single training image per person that will be used in the classification stage. The recognition rate is reached 96.3%.
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