PENDETEKSIAN OUTLIER PADA REGRESI LOGISTIK DENGAN MENGGUNAKAN TEKNIK TRIMMED MEANS
| dc.contributor.author | Sarimah | |
| dc.contributor.author | Sugiarto, Sigit | |
| dc.date.accessioned | 2017-01-20T08:02:09Z | |
| dc.date.available | 2017-01-20T08:02:09Z | |
| dc.date.issued | 2017-01-20 | |
| dc.description.abstract | This article discusses the outlier of logistic regression. The estimator is obtained through maximum likelihood method. Then numerical approach of Newton-Raphson method is applied. Furthurmore the coefficient of determination R2 is evaluated to interprete the dependent variables which are explained by the independent variables. The next step is the outlier detection by trimming of outlier estimate data in the side X, this technique is an idea from trimmed means. Trimming of data affects the regression model and upgrade the coefficient of determination R2. | en_US |
| dc.description.sponsorship | Sugiarto, Sigit | en_US |
| dc.identifier.uri | http://repository.unri.ac.id/xmlui/handle/123456789/8923 | |
| dc.language.iso | other | en_US |
| dc.subject | Logistic regression model | en_US |
| dc.subject | outlier | en_US |
| dc.subject | trimmed means | en_US |
| dc.subject | maximum likelihood method | en_US |
| dc.subject | Newton-Raphson method | en_US |
| dc.subject | coefficient of determination R2 | en_US |
| dc.title | PENDETEKSIAN OUTLIER PADA REGRESI LOGISTIK DENGAN MENGGUNAKAN TEKNIK TRIMMED MEANS | en_US |
| dc.type | student Paper Post Degree | en_US |