Name
Abstract | ||
|---|---|---|
The increasing number of user of mobile application, it is needed to check mobile applications that contains defect or not. I proposed a SVM method in comparison with CART and Test Metrics to classify classes in application. It shows that SVM method has better result in terms of precision and accuracy. SVM accuracy reaches 83% compared with CART and Test Metrics method in mobile apps defect prediction. |
Year | Venue | Field |
|---|---|---|
2016 | SOSE | Data mining,Computer science,Cart,Software bug,Support vector machine,Artificial intelligence,Accuracy and precision,Application software,Mobile apps,Machine learning |
DocType | Citations | PageRank |
Conference | 4 | 0.40 |
References | Authors | |
15 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Yoseph Ricky | 1 | 6 | 1.11 |
| Fredy Purnomo | 2 | 4 | 0.40 |
| Budi Yulianto | 3 | 4 | 1.07 |