Alimuddin, Alimuddin and Masjudin, Masjudin and Wiryadinata, Romi and Ningrum,, Oktavia (2022) Design and Development of California Papaya Murability Detection Based on Learning Vector Quantization Method Using LDR Sensor and Camera. In: Design and Development of California Papaya Murability Detection Based on Learning Vector Quantization Method Using LDR Sensor and Camera, 04 November 2021, Serang Banten Indonesia.

Text Alimuddin Co Author Pros Intern California Papaya LDR sensor Camera Des 2022.pdf Download (1MB)

Abstract

Sorting the ripeness of papaya fruit is generally done manually. Tech�nological developments can simplify and speed up the work of farmers in sorting papaya fruit, such as using the TCS3200 series LDR sensor, which produces red, green, and blue color frequency values. This sensor can distinguish ripe papaya fruit from different skin colors. Papaya with perfect green skin color is included in raw papaya, papaya with balanced green and yellow skin color means that papaya is mature, and papaya with even yellow skin color is included in ripe papaya. This category is also included in the class in the classification of papaya fruit maturity using the LVQ method. The data is taken directly using the camera by classifying it using the parameters of mean, skewness, and kurtosis. The results of the highest papaya ripeness classification accuracy are in the 2nd experiment with a learning rate value of 0.2 with hidden layer ten (10) and epoch 100, which is 93.3%, and the test results of the whole tool have an average success percentage value of 69.41%

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