Optimal Input Of Data Series In Predicted The Number Patient Of HIV-AIDS In East Java Province Using Multivariate Adaptive Regression Splines
| Main Author: | Herlina Jusuf |
|---|---|
| Format: | Penelitian |
| Terbitan: |
, 2015
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| Subjects: | |
| Online Access: |
http://repository.ung.ac.id/riset/show//1176/optimal-input-of-data-series-in-predicted-the-number-patient-of-hiv-aids-in-east-java-province-using-multivariate-adaptive-regression-splines.html |
Daftar Isi:
- Time series modelling is not linear, one of which is a Multivariate Adaptive Regression Splines (MARS). HIV AIDS is a serious issue on the health problems of the world currently and the future because the number of sufferer up increasing and not found vaccines and drugs for the prevention. Cases if HIV AIDS in East Java is the data series, and in MARS modelling needed in input. The purpose of this research is to determine the optimum input of the data series, and as criterion is the smallest GCV value. The result shows that significant lags on PACF is optimal input MARS modelling, because results the smallest GCV value. Prediction of the number of HIV AIDS sufferer is affected by the number of sufferer one, seven, and twelve previous period. Prediction of HIV AIDS with MARS modelling better than ARIMA.