Abstract :
ABSTRACT
Indonesia is one country that has great potential in agriculture. The high volume and value of export of guava fruit must be able to be balanced with an increase in the quality of processing and marketing. The thing to note is the quality standardization of agricultural products, especially guava fruit. The application of quality standardization will be able to produce products that have competitiveness and are able to penetrate various international markets. Guava fruit that is of high quality and meets the standards will be easily accepted by the market and has a high selling power. The maturity of the fruit when harvested is one of the important factors in maintaining quality. Fruit maturity is the condition of the fruit that is ready to be harvested and consumed directly or indirectly. In fact, it is often confused in choosing a guava fruit that has good maturity. Sometimes when sorting guava fruit is still using a manual method to distinguish the maturity of the guava fruit. Evalusai quality by observing visually has several disadvantages, including requiring a long time and producing quality products that are inconsistent because of the limitations of human visual, fatigue, and the presence of different perceptions of quality in each observer. With the method of classification of backpropagation artificial neural networks which results from the identification will display the quality of guava fruit according to the grouping. Image processing can be an alternative so that the problem can be resolved. The development of science and technology, image processing makes it possible to automatically sort agricultural and plantation products with the help of image processing applications. The purpose of this research is to produce a simple technology design that is expected to facilitate the guava fruit farmers and supermarket industries to sort.