<![CDATA[PT. A3 Karunia has been generating daily sales data but has not fully optimized its utilization, leading to a buildup of data. Therefore, data mining can be employed to address this issue. One of the data mining applications utilizes the Naïve Bayes method. This research develops a web-based prediction system using PHP and MySQL. The system utilizes 2 years' worth of sales data summarized into quarters. This results in a total of 8 quarters of sales data, which will serve as attributes in the Naive Bayes algorithm. The dataset used consists of 110 records, with 30% (32 records) designated as test classification data. By employing the Naive Bayes algorithm, classification results are obtained. The classification of test data yields an accuracy of 90.62%, with a breakdown of 3 misclassifications and the remaining 29 data points classified correctly.]]>
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