Judul: Prediksi Curah Hujan Bulanan menggunakan Teknik Jaringan Syaraf Tiruan
Abstrak: Metode Jaringan Syaraf Tiruan telah lama dimanfaatkan dalam prediksi curah hujan bulanan. Prediktor yang digunakan berupa curah hujan historis serta indeks ENSO wilayah Nino-3.4. Pada kenyataannya, keragaman curah hujan Indonesia tidak hanya dipengaruhi oleh ENSO, fenomena iklim IOD juga berperan, sehingga DMI sebagai indeks kejadian IOD dapat digunakan menjadi prediktor penduga curah hujan. Wilayah dengan pola curah hujan monsunal memiliki korelasi kuat terhadap prediktor indeks ENSO dan DMI, terutama pada periode Juni-November, sedangkan wilayah dengan curah hujan ekuatorial memiliki korelasi lebih rendah. Penerapan JST model 3 pola curah hujan monsunal menghasilkan R2 0.59-0.82 dan RMSE 0.04-0.09 dengan tingkat akurasi yang tinggi dibandingkan model lain. Sebaliknya, prediksi pada wilayah dengan curah hujan pola ekuatorial menghasilkan R2 rendah berkisar 0.13-0.37 dan RMSE lebih tinggi dibandingkan pola monsunal, yaitu 0.07-0.16. Rendahnya nilai R2 dan tingginya nilai RMSE menunjukkan bahwa keakuratan prediksi di stasiun pengamatan dengan pola hujan ekuatorial lebih rendah. Hal ini disebabkan oleh rendahnya pengaruh dari indeks ENSO dan IOD sebagai prediktor terhadap keragaman curah hujan di wilayah tersebut serta adanya limitasi model pada proses iterasi. Berdasarkan empat skenario model, semakin panjang periode prediksi yang dilakukan, maka tingkat ketepatan hasil prediski akan semakin berkurang.
Keyword: rainfall, prediction, artificial neural network, ENSO, IOD

Judul: Penerapan Jaringan Saraf Tiruan untuk Pemodelan Prakiraan Curah Hujan Bulanan
Abstrak: Rain is very usefull for life but heavy rainfall will lead to disaster if not anticipated properly. Rainfall forecasting is very usefull to anticipate the occurrence of extreme weather. This study developed artificial neural network models for the next three months rainfall forecasting. The data used in this study was the climate data from 1983 to 2013. The climate data used as model input were rainfall, temperature and relative humadity (RH). Temperature and RH averaged on a month period and observed three times a day. The best result from this study was the model with the highest correlation value. The Correlation values of the best model for rainfall forecasting of the next three months were 0.78, 0.83, 0.77 respectively.
Keyword: Bogor Agricultural University (IPB), temperature, RH, rainfall, ANN, forecast

Judul: Peptides Hydrolysate Derived from Collagen of Snakehead Murrel (Channa striata) Skin Demonstrate Anti-oxidant and Anti-cholesterol Activities.
Abstrak: Anti-cholesterol and anti-oxidant play crucial role to combat cardiovascular disease (CVD) related to formation of arterial plagues from oxidation of cholesterol. In the past decades, research on bioactive peptides demonstrating anti-cholesterol and anti-oxidant activities have been reported as the alternative drugs. In this study, acid soluble collagen was extracted from the skin of snakehead murrel and employed to induce production of collagenase by Bacillus licheniformis F11.4. The collagenases secreted were in turn purified through AKTA Purifier (ion exchange, DEAE column) and used to produce peptides hydrolysate. The purified enzymes were grouped in two distinct collagenase fractions, designated as fraction D and F. Peptides hydrolysate produced by the fraction D was found to demonstrate HMG-CoA inhibitor activity comparable to pravastatin and limited anti-oxidant activity. Meanwhile, peptides hydrolysate generated using the fraction F demonstrated anti-oxidant activity comparable to BHT (2mM), vitamin C (2mM) and vitamin E (2mM), but limited HMG-CoA activity. Combination of the fraction D and F resulted in substantial HMG-CoA inhibition and anti-oxidant activities.
Keyword: Anti-cholesterol, anti-oxidant, bioactive peptide, collagen, collagenase, snakehead murrel