PENGEMBANGAN METODE ANALISIS BEBAN KERJA WAKTU DALAM INTERPOLASI MENGGUNAKAN PENDEKATAN NON LINIER
Computational time for spatial interpolation is important to manage meteorological information effectively and efficiently. Therefore, this study aims to analyze the workload of computational time and gets the formulation for computational time based on three parameters: important numbers, resolutions, and the number of initial data points. Data used in this study is generated randomly by the 'runif' function in software R. The random data has 0, 3, and 6 decimal numbers. The number of points used is 10, 50, 100, 200, 500, 1000, 1500, 2000, 3000, 5000 and 8000 with the output resolution varies as follows: 0.5, 0.25, 0.05, 0.01 and 0.005. Consequently, the data are processed using different type of hardwares and softwares, and executed for Inverse Distance Weighted (IDW) interpolation. The computational time can be calculated by the point number (n) and resolution (r) values. The result shows that the time length (T) can be approximated by the equation: . Where the constants C1, C2, C3 and C4 differ according to software and hardware specifications. Using this approach, the computational time for spatial interpolation is expected to be studied better.
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