Penerapan Nilai Rata-Rata RGB Pada Aplikasi Pengukur Kematangan Buah Tomat

Abstract

Tomato is a fruit that grows in many tropical and subtropical areas. Tomatoes ripen very quickly, so improper handling can cause them to rot quickly. Distribution of tomatoes over long distances can cause quality degradation which can affect nutritional value. Farmers have many weaknesses to identify manual tomato ripeness due to factors such as fatigue, lack of motivation, experience, proficiency and so on. To solve this problem, the development of information technology allows identification of fruit maturity and even detection of fruit types with the help of computers. With the digital image, technology-based tomato maturity classification can be carried out. Therefore, in this study, the application of tomato maturity classification was carried out by applying the RGB average method to make it easier to determine the level of maturity of tomatoes. In this tomato maturity classification application, several processes are carried out, namely image reading, cropping, segmentation and RGB average calculation. There were 24 images of ripe tomatoes and 25 images of raw tomatoes used in the classification test for tomato maturity and the success rate was 95%.

Klasifikasi Kematangan Buah Tomat Dengan Metode Support Vector Machine

“…Beberapa fitur dari citra yang dapat di ekstraksi berupa ekstraksi tektur dan warna [4]. Klasifikasi kematangan buah tomat telah dilakukan diantaranya adalah dengan menghitung nilai rata-rata nilai RGB pada aplikasi pengukur kematangan buah tomat [5]. Selain itu klasifikasi kematangan buah tomat berdasarkan warnanya telah dilakukan dengan menggunakan algoritma Jaringan Syaraf Tiruan [6] oleh Humaira dkk.…”