<![CDATA[The delivery of logistics services continues to experience a rapid increase in line with the high sales of goods through e-commerce. According to the predetermined standards, each cargo expedition outlet is required to meet the monthly shipment achievement target (tonnage) to avoid fines and an increase in the target rate. This study aims to find out how to anticipate failure to achieve targets, so as to prevent additional operating expenses and profit instability. In this study, quantitative analysis was carried out using two algorithms. The Naïve Bayes algorithm is used to classify service user categories. The results showed that the industrial category contributed greatly to the delivery of cargo expeditions with a total tonnage percentage of 69.33%, while the remaining 30.67% was included in the individual category. Furthermore, the Multiple Linear Regression algorithm is used to predict profit values based on category classes. Predictions were made from October to December which resulted in an increase in profit for the individual category and a decrease in profit for the industrial category. Recommendations that can be made include royalty rewards for customers, brand awareness to attract new customers, as well as business cooperation with MSMEs and other business actors around them.]]>
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