PERBANDINGAN MODEL CURAH HUJAN LIMPASAN ANTARA METODE JARINGAN SYARAF TIRUAN DENGAN METODE SACRAMENTO
ABSTRACT: The rainfall-runoff
modeling is needed to fill in the data or make the data longer. Some method can
be used for forecast rainfall processing or runoff like sacramento or
artificial neural network (ann). The ann is one of artificial intelligent that
is an artificial representation of human’s brain which always try to simulation
learning process of its. This model is a black box model, so implementation did
not need complect science between many aspects in rainfall-runoff happened
process. The case study on the upstream of citarum river basin (saguling dam).
The data used are a rainfall data (11 rain station) , inflow and sediment rate
of month during 19 years from 1986 up to 2004. Rainfall data is input and
inflow rate is target output. This research use sacramento and reduced gradient
method. The result for training step sacramento’s method the correlation
is 81 % and reduced gradient’s method
the correlation is 99 %. For testing sacramento ‘s method the correlation is
83.22 % and reduced gradient’s method alternative 2 with four hidden node gives
the correlation is 65.57 %. For the next
step especially the artificial neural network method still need improvement so
that the artificial neural network can be used for modeling of rainfall runoff
process.
Penulis: DENNY YATMADI, NUZUL
BARKAH PRIHUTOMO
Kode Jurnal: jptsipildd140216
