—Palm oil is an important agricultural commodity as it has great contribution in producing vegetable oil. Being important commodity, palm oil is threatened by diseases that can attack since early stage. The diseases certainly disrupt the palm tree growth and may decrease the palm oil production. Technology can help in identifying disease in early stage so that effective treatment can be given immediately. This paper propose application of image processing and machine learning in identifying three palm oil diseases based on visual appearances. We design a method with linear complexity process in order to minimize processing time so that it can be implemented in mobile device. Using image processing, 6 types of features are extracted from palm leaf image then the pattern was learned using Neural Network method in machine learning process. The learning process yielded a classification model with 87.75% average accuracy and then a mathematical equation was formulated based on classification model in order to be implemented in mobile device.
—Image processing, machine learning, mobile device, neural network, palm oil disease.
The authors are with the aculty of Computer Science University of Indonesia (e-mail: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com, firstname.lastname@example.org).
Cite:Alham F. Aji, Qorib Munajat, Ardhi P. Pratama, Hafizh Kalamullah, Aprinaldi, Jodi Setiyawan, and Aniati M. Arymurthy, "Detection of Palm Oil Leaf Disease with Image Processing and Neural Network Classification on Mobile Device," International Journal of Computer Theory and Engineering vol. 5, no. 3, pp. 528-532, 2013.