Dimas Firmanda Al Riza (DFA)

         Pengenalan MATLAB Fungsi-fungsi dasar Operasi Matriks Deklarasi Variabel Visualisasi data 2D (plot) Simulasi Visualisasi data 3D (surf, contour) Contoh Model Ekosistem/Lingkungan/DAS Integrasi model matematis dan GIS

         Perintah dan kode dasar (clc, clear, whos, ;, dsb.) Operasi matematika dasar (+,-,/,\,*,^,.^) Perintah rangkap (menggunakan koma) Pembuatan/deklarasi variabel dan penggunaan String Variabel yang telah terdefinisi dalam MATLAB (ans, pi, inf, nan, sign, sqrt, exp, log, perintah trigonometri, pembulatan dan bilangan imajiner) Operasi matematika dengan menggunakan variabel Penjelasan format data pada MATLAB (Skalar, Vektor, Matrik) Matrik dan operasi matrik Plot grafik dasar (visualisasi)

    M-Files Flow control (pengaturan aliran data) Contoh flow control dengan M-Files menghasilkan data yang dapat di-plot dengan 3D Visualisasi 3D (surf, contour)

  Pemodelan Lingkungan Penjelasan PR3 (PR2 dengan MATLAB (Hidrograf))

     Read text data files Penjelasan PR3 Dynamic Data Entry GUI Matlab Mapping Toolbox

  Read .txt

load namafile.txt; a=namafile(:,1); b=namafile(:,2); c=namafile(:,3); … plot2.m

Read .xls

a=xlsread('namafile.xls'); b=a(:,1); c=a(:,2); d=a(:,3); … readexcel.m

http://blogs.mathworks.com/pick/200 7/08/13/video-series-reading-excel data-into-matlab-with-a-gui/

  Deklarasi Variabel Menentukan kondisi inisial

 Penghitungan

 Visualisasi 2D?

3D?

Labeling?

Legend?

 GUI sederhana untuk membaca dan memplot grafik bisakah.m

gui1.m

 The Mapping Toolbox imports and exports generic GIS data in several formats, including shapefile, TIFF/JPEG/PNG with work files, GeoTIFF (read only), and ARC ASCII Grid (read only) and it imports from various more specialized formats (DTED, USGS DEM, SDTS DEM, etc.). See Technical Note 2101 for information on geospatial data on the Internet: http://www.mathworks.com/support/tech notes/2100/2101.html

  Vector data Vector data use X and Y coordinates to define the locations of points, lines, and areas (polygons) that correspond to map features such as fire hydrants, trails, and parcels. As such, vector data tend to define centers and edges of features.

Raster data Raster data, on the other hand, use a matrix of square areas to define where features are located. These squares, also called pixels, cells, and grids, typically are of uniform size, and their size determines the detail that can be maintained in the dataset. Because raster data represent square areas, they describe interiors rather than boundaries as is the case with vector data.

 MATLAB Help Files

Thanks