OTOMATISASI TINGKAT KUALITAS KAYU KELAPA MENGGUNAKAN GENETIC ALGORITHM

Abstract

Coconut plantation in South Borneo had a total area of 30,513 ha with 26,633 tons of production result in the year of 2016. But South Borneo is still limited in the utilization of fruit part and leaf, whereas the coconut wood then was often used for construction material. The level of needs for coconut wood material in the industrial world were greatly increased. Indonesia is one of the exporter of coconut wood material into other countries. To determine good quality woods for best quality materials, control for the full process was necessary in order for the product to be ready to use. The visual determination of quality level (grading) for coconut wood need to be automated, with the result that could be used for determination of suitable material for furniture as well as building construction and deacrese the dependency for manual grader. This research produced the proposed enhancement methode for quality image recognition in a visual manner for coconut wood, Genetic Algorithm, that could obtain the necessary accuracy for the quality determination of coconut wood. The benefits of this research was to support coconut plantation on South Borneo in producing coconut wood material as one of the material industry commodities.