Implementasi Neural Network untuk Monitoring Level CPO dan Pengendalian Pompa Berbasis Arduino dan Aplikasi Android pada Tangki Bulking dalam Rangka Transformasi Industri 4.0 - Abdul Azis Rahmansyah; Ahmad Rizki Taufagus; Anna Angela Sitinjak; Golfrid Gultom (Politeknik Bosowa, 2025)
The application of automatic technology based on artificial intelligence is one of the important elements in supportingthe transformation towards Industry 4.0, especially in the palm oil industry sector. This study aims to develop a CrudePalm Oil (CPO) level monitoring system in a bulking tank using an ultrasonic sensor and automatically regulate thepump speed based on the classification of the Neural Network (NN) results implemented on an Arduino microcontroller.The designed system utilizes an HC-SR04 ultrasonic sensor to read the CPO surface height, then the data is processedthrough an artificial neural network model with one hidden layer containing three neurons and six output classes todetermine the pump speed level. The results of this conversion become a PWM signal which is used to control the pumpmotor through the motor driver. Testing was carried out 10 times with variations in liquid height, showing that the sensorhas a high level of accuracy with an average error of 0.13 cm. The NN model produces a classification accuracy of 100%on the test data, and the motor speed control runs proportionally to the liquid level. This system has proven to beresponsive and capable of controlling fluids efficiently and in real-time. The results of the study indicate that thisapproach is feasible to be applied for intelligent and adaptive automation of filling and emptying CPO tanks, in line withthe principles of Industry 4.0