Development Of Empty Oil Palm Fruit Bunches (EFB) Segregation Using Machine Learning

Mohamed Bukhary, Amsyar Arif (2018) Development Of Empty Oil Palm Fruit Bunches (EFB) Segregation Using Machine Learning. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

This project represents the development of empty oil palm fruit bunches (EFB) segregation prototype using MATLAB for the different age group. Most of the manufactured industry does not utilize the production by using the EFB according to suitable age. This problem occurs because the products do not have the good system to be implemented to segregate the EFB according to their age specification such as to improve the parameters for the machine to be operated. This is very crucial in the industry because the different age of EFB for making commercializes purposes and generate additional income to the palm oil company. The approach of this control system starts with building the high percentage of identification for each bunches belongs to which age group. The neural network is using the MATLAB software to train the parameter given and it automatically adjusts to the network's weights and biases. The system starts with after the drying process of the bunches after the milling process, MATLAB based of Neural Network as the threshold data to identify each bunches group and determine the sample of EFB to segregate according to their age specification.

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