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


Rainfall intensity can be measured one of them through the reading of the reflectivity of raindrops on the weather radar. Reflectivity values are represented through colors in the visualization of two-dimensional radar images. Based on several approaches to the classification of weather conditions through radar data that has been successfully carried out, a system is designed to classify rainfall according to weather conditions in an area by utilizing weather radar imagery.
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.

Keywords


Image processing; weather radar; ANFIS; cross validation

Full Text:

PDF


References

A. Prakasa and F. D. Utami, “Sistem Informasi Radar Cuaca Terintegrasi BMKG,” p. 11, 2019.
[2] D. S. Permana, T. D. F. Hutapea, A. S. Praja, and L. F. Muzayanah, “Pengolahan Multi Data Format Radar Cuaca Menggunakan Wradlib Berbasis Python,” vol. 17, no. 3, p. 8, 2016.
[3] F. Renggono, “Analisis Kemunculan Awan Hujan Berdasarkan Jenisnya untuk Mendukung Kegiatan Modifikasi Cuaca,” J. Sains Teknol. Modif. Cuaca, vol. 16, no. 2, p. 83, Dec. 2015, doi: 10.29122/jstmc.v16i2.1050.
[4] I. G. A. Gunadi and A. A. K. Dewi, “Klasifikasi Curah Hujan di Provinsi Bali Berdasarkan Metode Naïve Bayesian,” J. Mat., vol. 12, no. 1, p. 12, 2018.
[5] H. Liu and V. Chandrasekar, “Classification of Hydrometeors Based on Polarimetric Radar Measurements: Development of Fuzzy Logic and Neuro-Fuzzy Systems, and In Situ Verification,” J. ATMOSPHERIC Ocean. Technol., vol. 17, p. 25, 2000.
[6] M. I. Azhar and W. F. Mahmudy, “Prediksi Curah Hujan Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS),” p. 8, 2018.
[7] N. Faridatussafura and D. A. Rivai, “PEMANFAATAN PRODUK REFLECTIVITY RADAR CUACA DOPPLER C-BAND DI PANGKALPINANG UNTUK ESTIMASI CURAH HUJAN MENGGUNAKAN RELASI Z-R MARSHALL-PALMER DAN Z-R ROSENFELD TROPICAL,” p. 19, 2015.
[8] Hadriansa and D. Prayogi, “Pengenalan Citra Bola Robot BlueHuman G8,” Sebatik, vol. 22, no. 2, pp. 188–193, Dec. 2018.
[9] C. Z. van de Beek, H. Leijnse, P. Hazenberg, and R. Uijlenhoet, “Close-range radar rainfall estimation and error analysis,” Atmospheric Meas. Tech., vol. 9, no. 8, pp. 3837–3850, Aug. 2016, doi: 10.5194/amt-9-3837-2016.
[10] J. F. Fauzi, H. Tolle, and R. K. Dewi, “Implementasi Metode RGB To HSV pada Aplikasi Pengenalan Mata Uang Kertas Berbasis Android untuk Tuna Netra,” p. 7, 2018.
[11] M. Afrizal, “Klasifikasi Kondisi Lalu Lintas Menggunakan Algoritme Naïve Bayes Berbasis Data Twitter,” p. 55, Apr. 2018.
[12] V. T. Tran, B.-S. Yang, M.-S. Oh, and A. C. C. Tan, “Fault Diagnosis of Induction Motor Based on Decision Trees and Adaptive Neuro-fuzzy Inference,” Expert Syst. Appl., vol. 36, no. 2, pp. 1840–1849, Mar. 2009, doi: 10.1016/j.eswa.2007.12.010.



DOI: https://doi.org/10.22146/ijeis.57980

Article Metrics

Abstract views : 2646 | views : 3638

Refbacks

  • There are currently no refbacks.




Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Copyright of :
IJEIS (Indonesian Journal of Electronics and Instrumentations Systems)
ISSN 2088-3714 (print); ISSN 2460-7681 (online)
is a scientific journal the results of Electronics
and Instrumentations Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijeis.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijeis



View My Stats1
View My Stats2