PENYELESAIAN AKAR PERSAMAAN NON-LINEAR PADA RANGKAIAN SERI RLC OSILASI TEREDAM MENGGUNAKAN METODE SECANT

Solusi persamaan matematika yang sulit diselesaikan tidak bisa dilakukan dengan menggunakan metode analitik tetapi harus diselesaikan dengan metode numerik. Metode numerik merupakan suatu metode yang digunakan untuk memformulasikan persoalan matematika secara matematis dengan cara operasi aritmatika. Dalam metode numerik terdapat dua buah jenis sistem persamaan yaitu persamaan linear dan persamaan non-linear. Salah satu metode penyelesaian persamaan non-linear yaitu metode secant. Dalam penelitian ini, peneliti akan mencari akar persamaan non-linear dalam rangkaian seri RLC osilasi teredam menggunakan metode secant. Metode penelitian yang digunakan yaitu secara eksperimental dengan menggunakan perangkat pemprograman Matlab. Hasil diperoleh secara jelas dalam mengetahui akar persamaan non-linear pada rangakaian seri RLC osilasi teredam. 

VERIFICATION OF LAND MOISTURE ESTIMATION MODEL BASED ON MODIS REFLECTANCES IN AGRICULTURAL LAND

From this research, it is found that reflectances in the first, second, and sixth channels (R1, R2, R6) of MODIS have high correlations with surface soil moisture (percent weight) at 0-20 cm depth. An index called Land Moisture INdex (LMI) was created from the linier combination of R1 (percent), R2(percent), and R6 (percent). The MODIS reflectances and field soil moisture in paddy field taken from the Central and East Java during Juli-September 2005 are applied into the previous model which have been generated from data during July-September 2004. The result showed that there was a high correlation between Land/Soil Moisture (SM) which was measured from field survey, and LMI which was generated from the MODIS refectances. The best model equation between SM and LMI is the power regression model, which has the coeficient of determination of 88 percent. It is implied that soil moisture condition can be obtained from the MODIS data using LAnd Moisture Index. Therefore, the spatial information of drouht condition analysed throught the soil moisture in the agricultural land can be provided from the MODIS data. Keywords: Land Moisture Index, Soil Moisture Estimation, Spatial information, drought

Verification of Land Moisture Estimation Model Based on Modis Reflectances in Agricultural Land

From this research, it is found that reflectances in the first, second, and sixth channels (R1, R2, R6) of MODIS have high correlations with surface soil moisture (percent weight) at 0-20 cm depth. An index called Land Moisture INdex (LMI) was created from the linier combination of R1 (percent), R2(percent), and R6 (percent). The MODIS reflectances and field soil moisture in paddy field taken from the Central and East Java during Juli-September 2005 are applied into the previous model which have been generated from data during July-September 2004. The result showed that there was a high correlation between Land/Soil Moisture (SM) which was measured from field survey, and LMI which was generated from the MODIS refectances. The best model equation between SM and LMI is the power regression model, which has the coeficient of determination of 88 percent. It is implied that soil moisture condition can be obtained from the MODIS data using LAnd Moisture Index. Therefore, the spatial information of drouht condition analysed throught the soil moisture in the agricultural land can be provided from the MODIS data.p.46-54 : ilus. ; 30 c

Peluang dan tantangan aplikasi penginderaan jauh untuk mitigasi bencana

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