Naive Bayes classifier algorithm and Particle Swarm Optimization for classification of cross selling (Case study: PT TELKOM Jakarta)

Marketing has a broad range of strategies according to the needs of the company. One marketing strategy is cross-selling. The strategy can be done by offering new products. However, too many offers to customers who are not appropriate, make marketing nonoptimal. It is necessary for classification of existing telephone customers and speedy for cross-selling strategy IndiHome PT. TELKOM Jakarta. This study uses data mining classification with Naive Bayes classifier algorithm and selection of attributes' Particle Swarm Optimization to improve the classification accuracy. The result of Naive Bayes algorithm (85. 08%) can improve accuracy by using Particle Swarm Optimization as a selection attribute (89. 31%.