| The company already has report data related to the company's revenue achievements, but the information from this data is not used properly. Therefore, this research aims to determine the application of data mining to predict company revenue. The research methods used are the DES and TES methods, which process a set of unprocessed and undeveloped income data to create new information that is valuable and useful for the company, especially for company revenue generation. The research results show that the MAPE calculation using the DES method obtained a MAPE of 98.5, while the TES method obtained a MAPE of 5.42. With the smaller MAPE obtained, the TES method is more relevant in this research compared to the DES method, because the TES method has trends and seasonality so it is more accurate in its calculations compared to the DES method which only has trends. From the results of obtaining the MAPE, the TES method was used with a MAPE of 5.42. Based on the MAPE criteria, the ability to predict it is very good. |
