<![CDATA[Orange are very popular and consumed by most Indonesians. Oranges are the fruit with the second largest productivity in Indonesia. North Sumatra province is one of the areas with the highest number of citrus harvests. Buyers of oranges in North Sumatra generally taste oranges before buying because taste is the most important attribute according to consumer perceptions. After tasting the rsa citrus fruit and the taste is sweet, the buyer will immediately buy the orange juice. During the wrapping process, sometimes the seller will mix fruit with lower quality and unsweetened taste. So from these problems this research focuses on making a system that can classify the taste of citrus fruit. The classification process is carried out using the naive Bayes method. The classification process requires training data with three parameters, namely color, weight and diameter. Color data obtained with the TCS230 sensor, weight data using the load cell sensor and diameter data using the ultrasonic sensor. After the data is obtained, the classification process will be carried out. After the classification process is complete, the hasl will be displayed on the LCD. The naive Bayes classification was tested with 15 test data and produced an accuracy of 80%.]]>
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