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    Analisis Fase Tumbuh Padi Menggunakan Algoritma Ndvi, Evi, Savi, Dan Lswi Pada Citra Landsat 8

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    Paddy (Oryza sativa, sp) is including to a group of crops food which very important and useful for the life of the Indonesian people. One of regency in Central Java with a large of paddy production is Kendal regency. In 2013, paddy production in Kendal reached 234.557 tons by 45.221 hectares harvested area .In this globalization era, to support the information for food security program, required more quantitative high rate and accuracy of agricultural resources. Remote sensing technology is one of technology that can be utilized to obtain the high rate and accuracy of information about the agricultural resources. In this case, remote sensing technology can play a role by using temporal satellite images to determine the growth stage of paddy plants by looking at the vegetation index value of the paddy plant, so it can be estimated paddy harvested area annually.Based on the description above, the research conducted to analyze the phase of paddy growth in the Kendal area using remote sensing technology, where remote sensing is a technology that is ideally used considering several advantages such as wide coverage and fast.Some of the methods that have been used for determine vegetation index are NDVI, EVI, SAVI, and LSWI. Furthermore, these methods will be used for trying to determine the phase of paddy growth. In this study will be analyzed which method that has the best model for determining the phase of paddy growth. Then concluded that the NDVI has a modeling method which better than other methods. The coefficient of determination (R2) of NDVI is 0,868 with obtained model is y = - 0,0199X2 + 0,2298X + 0,0539.According to the results of Landsat 8 satellite image processing using NDVI method and NDVI modeling that has been done to the recording image in May 2015, the estimation result of paddy harvested area on Kendal regency about 1872,655 Ha. Keywords : The phase of paddy growth, Landsat 8 Satellite Imagery, Vegetation Index, Harvested area. *) Penulis, Penanggungjawa
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