Rancang Bangun Sistem Deteksi Tingkat Kemanisan Buah Melon (Sky Rocket) dengan Metode Gray Level Co-Occurrence Matrix (GLCM) dan Decision Tree - Kelvin Himawan Eka Maulana; Fitri Utaminingrum (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2022)
Melon fruit has a sweet fruit taste, thick flesh, and disease resistance. A good quality melon has the characteristics of the outer skin not breaking or cracking, the flesh is free from internal bruising and browning, and the fruit is free from diseases that affect the general appearance. For diabetics, choosing a sweet melon will certainly cause problems. To determine the level of sweetness of the melon, it is first split to take a sample of the liquid and tested on a refractometer. This is certainly not practical, so innovation is needed to determine the level of sweetness of melons by processing the image with a digital image processing process. This study uses a digital image processing process by distinguishing the sweetness level of melons into 3 classes, namely low sweetness level, medium sweetness level, and high sweetness level. Method of Gray Level Co-occurrence Matrix used in this study to perform feature extraction using 5 features that correlation, Contrast, homogeneity, dissimilarity, and Energy with variations in the distance d= 1,2,3,4 and angle θ= 0°,90°,180°,270°. In the melon sweetness classification method, Decision Tree is used to distinguish low, medium, and high sweetness classes. This study used 435 data sets with 390 training data and 45 test data resulting in an accuracy of 80% at low sweetness level, 73% at medium sweetness level and 80% at high sweetness level. The best average computing time obtained at the low sweetness level is 3.87 seconds.