ALGORITMA K-MEANS CLUSTERING DALAM PENGOLAHAN CITRA DIGITAL LANDSAT
| Main Authors: | Apriyanti, Nur Ridha, Nugroho, Radityo Adi, Soesanto, Oni |
|---|---|
| Other Authors: | Ilmu Komputer, ULM, Unlam, Universitas Lambung Mangkurat |
| Format: | Article info eJournal |
| Bahasa: | eng |
| Terbitan: |
Lambung Mangkurat University
, 2016
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| Online Access: |
http://klik.unlam.ac.id/index.php/klik/article/view/22 http://klik.unlam.ac.id/index.php/klik/article/view/22/20 |
Daftar Isi:
- Digital image processing can now be done with a variety of assistive software, one of which ArcGIS. At ArcGIS there are some features of image classification with multiple algorithms, but there is an algorithm that has not been used, this is K-Means algorithm. From the test results are obtained 12 land cover classes as follows pastures, airports, mining, open land, plantations, swamps, bushes, shrubs, settlements, plantations, dryland agriculture, and vegetated land. Results of field inspections showed 94.4% fit, and 5.6% did not correspond to actual field conditions. Keywords : Digital Image Processing, K-Means Algorithm, Clustering. Pengolahan citra digital saat ini bisa dilakukan dengan berbagai macam software bantu, salah satunya ArcGIS. Pada ArcGIS terdapat beberapa fitur klasifikasi citra dengan beberapa algoritma, namun ada satu algoritma yang belum digunakan yaitu algoritma K-Means. Dari hasil pengujian didapatkan 12 kelas penutupan lahan sebagai berikut padang rumput, bandara udara, pertambangan, lahan terbuka, hutan tanaman, rawa, semak, belukar, pemukiman, perkebunan, pertanian lahan kering, dan lahan bervegetasi. Hasil pengecekan lapangan menunjukkan 94,4% sesuai, dan 5,6% tidak sesuai dengan kondisi lapangan yang sebenarnya. Kata kunci : Pengolahan Citra Digital, Algoritma K-Means, Clustering