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Klasifikasi Curah Hujan Menggunakan Neuro-Fuzzy System Melalui Citra Radar Cuaca
https://doi.org/10.22146/ijeis.57980 Bagaskara Ilham Abadi(1*), Raden Sumiharto(2)
(1) Program Studi Elektronika dan Instrumentasi, FMIPA, UGM, Yogyakarta
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
The system implementation is carried out in several stages, namely pre-processing, feature extraction and labeling, and classification. Pre-processing is done to visualize radar data from Yogyakarta Climatology Station into a two-dimensional image. After capturing features using the RGB and HSV methods and labeling the rain class, classification is performed using the Neuro-fuzzy algorithm with the Adaptive Neuro-fuzzy Inference System (ANFIS) architecture. The results showed that the Neuro-fuzzy System algorithm was able to classify rainfall better on the RGB feature with an accuracy of 85.02% and a precision of 86.19%, while for the HSV feature the accuracy was 82.68%, 86.67% precision.
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DOI: https://doi.org/10.22146/ijeis.57980
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