KOMBINASI SELF-ORGANIZING MAP NEURAL NETWORK DAN K-NEAREST NEIGHBOR UNTUK KLASIFIKASI OTOMATIS CITRA KELOMPOK BINTIK MATAHARI
| Main Authors: | Satiabudhi, Gregorius, Adipranata, Rudy, Anwar, Bachtiar, Setiahadi, Bambang, T, ALVIN NATHANIEL |
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| Format: | Proceeding PeerReviewed application/pdf |
| Terbitan: |
, 2011
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| Subjects: | |
| Online Access: |
https://repository.petra.ac.id/15900/1/Publikasi1_02030_174.pdf http://knsi2011.stikom-bali.ac.id/ https://repository.petra.ac.id/15900/ |
Daftar Isi:
- Observation and forecasting of weather disturbances in the earth and space caused by the appearance of sunspots is one of the tasks of the LAPAN. The sunspots are actually a tremendous explosion (flares) and coronal mass ejection (CME) that may affect electromagnetic field in a location on the earth. In order to support an early warning system that will be made, LAPAN wishes to make a computer application that can automatically classify a group of sunspots. Here we classify groups of sunspots on a sun digital image based on the Modified - Zurich Sunspot Classification System. In this paper we present our experiment results on the sunspots group classification using the combination of Self-Organizing Map Neural Networks and K-Nearest Neighbor. The result of testing is promising because the classification accuracy was 100 for the data that is trained and 89.1 for the data that is not trained.