dc.contributor.author | Hidayat, Muhamad Arief | |
dc.contributor.author | Djunaidy, Arif | |
dc.date.accessioned | 2016-06-09T04:12:28Z | |
dc.date.available | 2016-06-09T04:12:28Z | |
dc.date.issued | 2016-06-09 | |
dc.identifier.issn | 20853092 | |
dc.identifier.uri | http://repository.unej.ac.id/handle/123456789/74656 | |
dc.description | Jurnal SPIRIT Vo.7 No.1 Mei 2015, hal 14-22 | en_US |
dc.description.abstract | The classification method based on data gravitation (DGC) is one of the new classification techniques that uses data gravitation as the criteria of the classification. In the case of DGC, an object is classified on the basis of the class that creates the largest gravitation in that object. However, the DGC method may cause inaccurate result when the training data being used suffer from the class imbalanced problem. This may be caused by the existence of the training data containing a class having excessively big mass that will in turn tend to classify an uknown object as a member of that class due to the hight degree of the data gravitation produced, and vice versa. | en_US |
dc.language.iso | id | en_US |
dc.subject | data gravitation-based classification | en_US |
dc.subject | class imbalanced problem | en_US |
dc.subject | posterior probability | en_US |
dc.title | Klasifikasi Berbasis Gravitasi Data dan Probabilitas Posterior | en_US |
dc.type | Article | en_US |