Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu
Education at this time is an important requirement in facing the demands of an increasingly advanced era in technolo-gy. To compensate this, the existing educational standards in universities must also be improved, this is a bit much affect the pattern of teaching from universities that produce qual...
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| Format: | Article |
| Language: | English |
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P3M Politeknik Negeri Banjarmasin
2018-01-01
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| Series: | Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer |
| Subjects: | |
| Online Access: | http://eltikom.poliban.ac.id/index.php/eltikom/article/view/29 |
| _version_ | 1818851847783317504 |
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| author | Yohakim Benedictus Samponu Kusrini Kusrini |
| author_facet | Yohakim Benedictus Samponu Kusrini Kusrini |
| author_sort | Yohakim Benedictus Samponu |
| collection | DOAJ |
| description | Education at this time is an important requirement in facing the demands of an increasingly advanced era in technolo-gy. To compensate this, the existing educational standards in universities must also be improved, this is a bit much affect the pattern of teaching from universities that produce qualified graduates who can compete in the world of work later and indirectly give a positive impact on the university itself. Qualified graduates are of course not only depending on the role of a university but also majors and quality of education as long as students are still in high school / vocational school also plays an important role. Results of the on-time graduation rate prediction research can be used as an information to im-prove the quality and optimization of the education system but it requires a maximum degree of accuracy. This research predicts on time graduation rates by conducting analysis using data mining classification techniques. Naïve Bayes algo-rithm that are used for this research will be discussed as a reference in conducting research. The author performs a series of different experimental scenarios / cross validation to perform comparisons that can give a difference in the level of ac-curacy gained from this research. The results of this research indicate that with the addition of Cross Validation testing scenario there is an increase of 2% accuracy of the test. |
| first_indexed | 2024-12-19T07:11:32Z |
| format | Article |
| id | doaj.art-af9bb90c7b734c5681b00e044abc6465 |
| institution | Directory Open Access Journal |
| issn | 2598-3245 2598-3288 |
| language | English |
| last_indexed | 2024-12-19T07:11:32Z |
| publishDate | 2018-01-01 |
| publisher | P3M Politeknik Negeri Banjarmasin |
| record_format | Article |
| series | Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer |
| spelling | doaj.art-af9bb90c7b734c5681b00e044abc64652022-12-21T20:31:11ZengP3M Politeknik Negeri BanjarmasinJurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer2598-32452598-32882018-01-0112566310.31961/eltikom.v1i2.2929Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat WaktuYohakim Benedictus Samponu0Kusrini Kusrini1Universitas Amikom YogyakartaUniversitas Amikom YogyakartaEducation at this time is an important requirement in facing the demands of an increasingly advanced era in technolo-gy. To compensate this, the existing educational standards in universities must also be improved, this is a bit much affect the pattern of teaching from universities that produce qualified graduates who can compete in the world of work later and indirectly give a positive impact on the university itself. Qualified graduates are of course not only depending on the role of a university but also majors and quality of education as long as students are still in high school / vocational school also plays an important role. Results of the on-time graduation rate prediction research can be used as an information to im-prove the quality and optimization of the education system but it requires a maximum degree of accuracy. This research predicts on time graduation rates by conducting analysis using data mining classification techniques. Naïve Bayes algo-rithm that are used for this research will be discussed as a reference in conducting research. The author performs a series of different experimental scenarios / cross validation to perform comparisons that can give a difference in the level of ac-curacy gained from this research. The results of this research indicate that with the addition of Cross Validation testing scenario there is an increase of 2% accuracy of the test.http://eltikom.poliban.ac.id/index.php/eltikom/article/view/29data mining, Cross Validation, Naïve Bayes |
| spellingShingle | Yohakim Benedictus Samponu Kusrini Kusrini Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer data mining, Cross Validation, Naïve Bayes |
| title | Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu |
| title_full | Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu |
| title_fullStr | Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu |
| title_full_unstemmed | Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu |
| title_short | Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu |
| title_sort | optimasi algoritma naive bayes menggunakan metode cross validation untuk meningkatkan akurasi prediksi tingkat kelulusan tepat waktu |
| topic | data mining, Cross Validation, Naïve Bayes |
| url | http://eltikom.poliban.ac.id/index.php/eltikom/article/view/29 |
| work_keys_str_mv | AT yohakimbenedictussamponu optimasialgoritmanaivebayesmenggunakanmetodecrossvalidationuntukmeningkatkanakurasiprediksitingkatkelulusantepatwaktu AT kusrinikusrini optimasialgoritmanaivebayesmenggunakanmetodecrossvalidationuntukmeningkatkanakurasiprediksitingkatkelulusantepatwaktu |