Journal ID : TRKU-07-08-2020-10976
[This article belongs to Volume - 62, Issue - 07]
Total View : 433

Title : Design and Implementation System Sorting Tomato (Lycopersicum Esculentum) With Learning Vector Quantization

Abstract :

Tomato is a fruit that is consumed every day by the Indonesia population Identification of maturity of tomatoes in general is still mostly done manually by farmers. The development of information technology enables the identification of fruit maturity level based on ciitra with the help of computer. This computational way is done by using the camera as an image processor of the recorded image (image processing). The tomato fruit is identified based on the image HSV input obtained from the capture result, after obtaining the HSV for its quality detection. From several samples of grayscale data pattern of tomato fruit with different quality levels obtained by several groups of maturity level, some of the maturity level will be clarified with Learning Vector Quantization algorithm with HSV data is processed into HSV data and classified by this algorithm to get maturity level and accurate quality. This system has accuracy 76.67%

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