This research provides an analysis of tourism potential in Pekalongan Regency based on Twitter media so that it can provide input for related agencies to develop new potential tourism objects. Decision tree method with C4. 5 is used to classify positive reviews where tourists will visit again and vice versa negative reviews with tweet data parameters related to tourism object, like location access, service satisfaction, conditions and functionality of existing facilities, and shopping experiences. The results of the review classification from the decision tree serve as input to the promotion strategy to be applied in the website media. Training data collection of 250 tweets related to the name of the tourism object in Pekalongan Regency was conducted and the experimental process was carried out in testing the model using RapidMiner 5.3. Stratified sampling with the C4. 5 Decision Tree obtained the highest accuracy rate of 92% using fold= 6: 4. 20 tweet sampling tests related to the Welo Asri Petungkriyono found 17 positive review tweets with the most words related to the condition and functionality of existing facilities and 3 negative reviews related to location access and service satisfaction.