Abstract
Coffee is an agricultural product highly favored by the majority of the Indonesian population. Coffee comes in various types, each with a distinct aroma. Currently, differentiating coffee types relies on conventional methods, using the human nose, which is shubjective and dependent on individual conditions. This approach is less effective. To address this, researcher have developed a machine learning based system using Arduino Mega 2560 as the microcontroller, gas sensor MQ4, MQ7, MQ135, as the aroma detection tools, and the Linear Discriminant Analysis (LDA) algorithm as the classification method. The results of this system can classify 5 types of coffee with an accuracy rate of 90%.
Published Version
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