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Journal : INFOKUM

Tea Leaf Pest Detection Using Support Vector Machine (SVM) METHOD IN PTPN IV Unit Bah Butong Steven Steven
INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

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Abstract

Indonesia is one of the largest tea-producing countries in the world. The Ministry of Trade recorded the value of tea exports in 2017 of 1,826.8 million US dollars. So that the quality and quality of the tea produced must be considered, starting from planting tea plants, picking tea leaves, to processing tea leaves into ready-to-eat tea. So far, farmers are only picking tea leaves based on the time they are picked from the planting block. If the time to pick the block has arrived, then the block will be picked as a whole. Weather is one of the factors that affect the uncertainty of picking times. This study identified pests on tea leaves using digital image processing. The first stage starts with image acquisition and preprocessing. From the results, the statistical characteristics of each image are taken. The data resulting from the training image are stored in a database. The training image data will be used as a reference for identifying types of pests using a Support Vector Machine