Perancangan Automatic Sorting Conveyor Berdasarkan Kematangan Buah Sawit Menggunakan Algoritma Neural Network - Wahyudi, Ilham; Satria, Habib (Riau Jurnal Teknik Informatika, 2025)
The goods sorting system is one of the important processes in the logistics system, especially when applied to work in the palm oil processing industry. The problem that occurs in the ripeness of palm fruit is that palm oil farmers find it difficult to distinguish the level of ripeness of palm fruit which will later affect the selling price of palm oil. Therefore, an automatic sorting conveyor control system is designed using an Arduino microcontroller to detect the level of ripeness of palm fruit by applying the neural network algorithm method in identifying the type of palm fruit based on the level of ripeness of the palm fruit. Then the integration of several sensors connected to the Arduino will later make it easier for the servo motor to determine the ripeness of the palm fruit. The results obtained using the neural network algorithm in processing the level of accuracy in identifying raw or ripe palm fruit can operate with the program settings that have been designed. In the Matlab simulation with the neural network method, an image pattern is obtained where if the result is close to 1 then the palm fruit is ripe, otherwise if there is nothing close to the value 1 then the palm fruit is still raw. The recorded data can later be a reference for palm oil farmers in making sales more accurately.