| Autor: |
Edi Sutoyo, Oktariani Nurul Pratiwi, Rizqi Prima Hariadhy |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
International Conference on Emerging Applications and Technologies for Industry 4.0 (EATI’2020) ISBN: 9783030802158 |
| DOI: |
10.1007/978-3-030-80216-5_7 |
| Popis: |
Television is the most effective marketing media and is the choice of advertisers today. One parameter that is a measure of the success of a television is the rating of the programs on the television. This parameter is also the consideration of advertisers in choosing a television station. For companies engaged in the advertising industry generally will provide offers to prospective customers using historical data related to ratings that have been obtained. However, the company has not been able to provide rating predictions in the future with a rational method. One approach to overcoming this problem is to apply one of the techniques in data mining, the K-nearest neighbor algorithm. The results showed that the K-nearest neighbor was able to classify television advertising ratings with an accuracy of 91.18%. This achievement shows that the K-nearest neighbor algorithm remains powerful used for the classification of television advertising ratings. The results of this study can provide one of the options for advertising companies to provide offers related to the prediction of television ratings to advertisers as one of the considerations in choosing a television station. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
