Rizki, Khairur
University Of Putra Indonesia YPTK Padang

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Identification Rainfall Humidity With Sugeno Methods Rizki, Khairur
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 4, No 2 (2018)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v4i2.11266

Abstract

Moisture identification of rainfall is very useful and petrified in the activity of utilizing the sun's heat, such as in drying clothes, drying food ingredients in household businesses, and so on. Rainfall is influenced by changes in temperature and humidity that is always changing. To predict the accuracy of rainfall in this study used the Fuzzy Sugeno method. In the Fuzzy Sugeno method, input data in the form of rainfall data, light intensity, and temperature, while output data in the form of humidity indications of rainfall with an indication of damp, very humid, and not humid. In order for all input data to be classified, the Arduino module is used to translate the results of reading input data from the sensor. The accuracy of the prediction of identification of rainfall from the results of this study is very good. So this research is very helpful in identifying the level of humidity in the rainfall.