Estimasi Curah Hujan Kota Banjarbaru Kalimantan Selatan Menggunakan Metode Jaringan Syaraf Tiruan

Abstract: Rain is weather phenomenon caused by climate’s physical conditions of atmosphere variables such as temperature, air pressure, air density, humidity and wind of velocity. Many researches on rain have been undertaken in Indonesia. Many statistic models are resulted from those researches; nevertheless, in statistic models climate’s physical conditions are not considered as components which affect the rain occurrence. Besides, estimating the amount of rain that is to fall-whether it is increasing, decreasing, or static- with statistic models is still unsure. Physical and mathematical approaches of weather variables only are not enough to estimate rainfall. More interpretations are needed to apply. Therefore, this research implements a way to estimate daily rainfall using a method called Artificial Neural Network. As parameter of the inputs of JST program, then the data of daily temperature, air humidity and wind speed play important roles, while the output which is manifested in daily rainfall tested in data scale, a period of 5-9 years. The results obtained show that JST method enables us to estimate daily rainfall of Kota Banjarbaru.
Keywords: estimation, daily rainfall, Artificial Neural Network
Penulis: Muhammad Rizalihadi, Simon S Siregar dan Sudarningsih
Kode Jurnal: jpfisikadd090071

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Jp Fisika dd 2009