DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM
Twin Bounded SVM (TB-SVM) is an improvement of the Twin SVM method and has advantages in classification problems compared to standard SVM. In this research, linear TB-SVM and nonlinear TB-SVM methods will be applied to detect drug use based on 23 symptoms experienced. The training and testing data i...
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Universitas Pattimura
2021-12-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4260 |
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| author | Berny Pebo Tomasouw Yopi Andry Lesnussa |
| author_facet | Berny Pebo Tomasouw Yopi Andry Lesnussa |
| author_sort | Berny Pebo Tomasouw |
| collection | DOAJ |
| description | Twin Bounded SVM (TB-SVM) is an improvement of the Twin SVM method and has advantages in classification problems compared to standard SVM. In this research, linear TB-SVM and nonlinear TB-SVM methods will be applied to detect drug use based on 23 symptoms experienced. The training and testing data is divided into three partition data schemes (60/40 scheme, 70/30 scheme and 80/20 scheme) in order to determine the best level of accuracy that can be obtained. The test results show that the nonlinear TB-SVM with the RBF kernel has a better accuracy rate than the linear TB-SVM, that is 80% at 60/40 scheme, 90% at 70/30 scheme, and 95% at 80/20 scheme. |
| format | Article |
| id | doaj-art-8478ddb892ef49528a3aaf863b4dc799 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2021-12-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-8478ddb892ef49528a3aaf863b4dc7992025-08-20T03:36:12ZengUniversitas PattimuraBarekeng1978-72272615-30172021-12-0115475376010.30598/barekengvol15iss4pp753-7604260DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVMBerny Pebo Tomasouw0Yopi Andry Lesnussa1Jurusan Matematika FMIPA Universitas PattimuraUniversitas PattimuraTwin Bounded SVM (TB-SVM) is an improvement of the Twin SVM method and has advantages in classification problems compared to standard SVM. In this research, linear TB-SVM and nonlinear TB-SVM methods will be applied to detect drug use based on 23 symptoms experienced. The training and testing data is divided into three partition data schemes (60/40 scheme, 70/30 scheme and 80/20 scheme) in order to determine the best level of accuracy that can be obtained. The test results show that the nonlinear TB-SVM with the RBF kernel has a better accuracy rate than the linear TB-SVM, that is 80% at 60/40 scheme, 90% at 70/30 scheme, and 95% at 80/20 scheme.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4260twin boundedsvmdrugsdetection |
| spellingShingle | Berny Pebo Tomasouw Yopi Andry Lesnussa DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM Barekeng twin bounded svm drugs detection |
| title | DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM |
| title_full | DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM |
| title_fullStr | DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM |
| title_full_unstemmed | DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM |
| title_short | DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM |
| title_sort | deteksi penyalahgunaan narkoba dengan metode twin bounded svm |
| topic | twin bounded svm drugs detection |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4260 |
| work_keys_str_mv | AT bernypebotomasouw deteksipenyalahgunaannarkobadenganmetodetwinboundedsvm AT yopiandrylesnussa deteksipenyalahgunaannarkobadenganmetodetwinboundedsvm |