Sistem Pendeteksi Kematangan Buah Apel menggunakan Metode Naive Bayes berbasis Embedded System - Irvan Ramadan; Dahnial Syauqy; Rakhmadhany Primananda (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
Apple fruit is one of the many types of fruit that has many benefits including preventing disease, nourishing the body and can lose weight. In general, some apple sellers are still unable to distinguish in the selection of apples with the right maturity level, while the human accuracy is not all the same. Everyone has different perceptions in making assessments. Also not everyone has a sharp sense of vision to color. Therefore, a study was made on a system that can classify the level of maturity of apples using the naive Bayes method. This method is a method that is quite good in classifying because the classes to be used are predetermined. In this study, the apple used was Rome Beauty. The level of maturity based on color and weight can be divided into three, namely raw green and ripe reddish yellow and foul yellow cloudy. The sensor readings are processed on the Arduino Uno microcontroller. The results obtained from this study are the level of accuracy on the load cell weight sensor of 96.09% and the level of accuracy on the color sensor of 96.67%. Also obtained the level of accuracy of the calculation of the naive Bayes classification of 100% and the system execution time with an average of 0.725 seconds.