PENGELOMPOKKAN HABITAT DASAR PERAIRAN DANGKAL BERBASIS DATA SATELIT QUICKBIRD MENGGUNAKAN ALGORITMA SELF ORGANISING MAP

Authors

  • Asmadin Asmadin Fakultas Perikanan dan Ilmu Kelautan Universitas Haluoleo
  • Vincentius P Siregar Departemen ITK FPIK IPB Bogor
  • Antonius Bambang Wijanarto Bakosurtanan Cibinong

Abstract

Pengembangan algoritma self organising map dalam penelitian ini bertujuan untuk mengelompokkan habitat perairan dangkal berbasis data satelit Quickbird. Data primer dikumpulkan melalui data penginderaan jauh dan survey lapang, sedangkan data sekunder dikumpulkan dari penelitian yang relevan. Hasil penelitian menunjukkan bahwa klasifikasi algoritma self organising map dapat mengklaster/ mengklasifikasi citra Quickbird dari berbagai kombinasi kanal. Dari berbagai kombinasi input data setelah direduksi kolom air dengan algoritma Lyzenga, Self organising map menunjukkan hasil klaster yang relatif baik. Algoritma Lyzenga dapat mengelompokkan habitat perairan dangkal 6 (enam) kelas habitat, yaitu karang mati (merah), karang hidup (hijau), lamun (orange), pasir (kuning), dan habitat campuran (hijau muda), daratan (hitam) dan perairan (biru). Setelah menggunakan self organising map secara visual terlihat 6 kelas habitat yang berbeda dari Lyzenga, yaitu karang mati (kuning), karang hidup (cyan), lamun (ungu), pasir (kuning), dan habitat campuran (biru), daratan (hijau) dan perairan (coklat). Algoritma self organising map dapat mengurangi kesalahan tematik habitat perairan dangkal dan sangat membantu proses ekstraksi ROI (region of interset) untuk reklasifikasi lebih lanjut dengan teknik klasifikasi supervised.

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Published

2012-08-14

How to Cite

Asmadin, A., Siregar, V. P., & Wijanarto, A. B. (2012). PENGELOMPOKKAN HABITAT DASAR PERAIRAN DANGKAL BERBASIS DATA SATELIT QUICKBIRD MENGGUNAKAN ALGORITMA SELF ORGANISING MAP. AQUASAINS, 1(1), 9–16. Retrieved from http://jurnal.fp.unila.ac.id/index.php/JPBP/article/view/8

Issue

Vol. 1 No. 1 (2012)

Section

Articles

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