<![CDATA[Cocoa (Theobroma cacao Linn) is one of the leading export commodities of plantations in Indonesia. To maintain the quality of cocoa commodities, the government enforces the rules of SNI 2323-2008 regarding the quality standards of cocoa beans. The special requirements in the regulation divide cocoa bean into 3 classes, namely: Kelas Mutu I, Kelas Mutu II, and Kelas Mutu III. The aroma quality of cocoa beans is one of the standards contained in the regulation. So far, the quality of cocoa bean aroma has been identified using a human tester, which has the weakness of being unstable and subjective. With the development of technology, an electronic nose consisting of a series of gas sensors can analyze and recognize the characteristics of complex gas samples. So this research was carried out by making a classification system for the quality of cocoa beans based on their aroma using an electronic nose. The classification system used to measure quality of cocoa beans uses the Artificial Neural Network (ANN) method, to identify patterns in identifying the type of quality of cocoa beans based on their aroma. The electronic nose system was built using 3 gas sensors, namely: MQ 2, MQ 3, and MQ 135. The data processing and classification of ANN implementation were carried out using Arduino MEGA 2560. The results showed that the ANN method was able to identify the type of quality of cocoa beans with a success rate of 77.78 % and the average computation time required is 1.1317244 seconds.]]>
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