Classification of maturity level of fuji apple fruit with fuzzy logic method
Evi Mulyani, Jeni Poniman Susanto
Aug 1, 2017
Citations
8
Citations
Journal
2017 5th International Conference on Cyber and IT Service Management (CITSM)
Full text
Semantic Scholar
Key Takeaway Key Takeaway: The fuzzy model accurately classifies fuji apples into raw, half-ripe, and ripe maturity levels, with a level of accuracy of 91.66% for training data and 85.71% for testing data.
Abstract
Color is one of the attributes that play a role in identifying specific objects, color processing including the extraction of information about the spectral properties of the object's surface and look for the best similarity of a set of descriptions which have been known to do an introduction. Therefore, the classification is needed right fuji apples to obtain good quality fruit. Fuzzy model is one method that can be used to determine the maturity classification fuji apples. This study aims to apply fuzzy model in the classification level of maturity fuji apples and describe the level of accuracy. The process is done is to change the type of fuji apples picture of the type red green blue (RGB) to the type of grayscale used as research data. Furthermore, the extraction is done using MATLAB help to obtain information from images. The result of the fuzzy model is the value for the level of maturity fuji apples are divided into three categories: raw, half-ripe and ripe. Level accuracy of 91.66% for the training data with error 8.34% and 85.71% of data testing with a 14.29% error.