Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5
<p class="BodyAbstract">The student is one of entities in University or Higher Education. The student has a variety of data, such as self-identity information such as address, type of school, work of parents, type of class, etc. In fact many students whose graduation rate is differen...
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| Format: | Article |
| Language: | English |
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University of Darussalam Gontor
2017-11-01
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| Series: | Fountain of Informatics Journal |
| Subjects: | |
| Online Access: | https://ejournal.unida.gontor.ac.id/index.php/FIJ/article/view/1067 |
| _version_ | 1828055607980064768 |
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| author | Indah Puji Astuti |
| author_facet | Indah Puji Astuti |
| author_sort | Indah Puji Astuti |
| collection | DOAJ |
| description | <p class="BodyAbstract">The student is one of entities in University or Higher Education. The student has a variety of data, such as self-identity information such as address, type of school, work of parents, type of class, etc. In fact many students whose graduation rate is different, on time and not on time. The number of students who graduate is not on time will be a problem not only for university but also for faculty. The number of students graduating each year is one of points of assessment when faculty or study program submits accreditation. C4.5 Algorithm is one of classification algorithm with decision trees. In this study conducted an analysis of student data Engineering Studies Program University of Muhammadiyah Ponorogo 2012/2013. The decision trees in this case is useful for exploring student data, finding the hidden relationship between a number of candidate input attributes with a target attribute. The input attribute consist of, the type of school, address, work of parent, and type of class. The output attribute to classify is status, which consists of "on time" and "not on time". The results from this analysis shown that in this case the C4.5 algorithm can predict with an accuracy value only 82%.</p> |
| first_indexed | 2024-04-10T20:42:23Z |
| format | Article |
| id | doaj.art-291efdc997f84551b16f6a3fc6773bb9 |
| institution | Directory Open Access Journal |
| issn | 2541-4313 2548-5113 |
| language | English |
| last_indexed | 2024-04-10T20:42:23Z |
| publishDate | 2017-11-01 |
| publisher | University of Darussalam Gontor |
| record_format | Article |
| series | Fountain of Informatics Journal |
| spelling | doaj.art-291efdc997f84551b16f6a3fc6773bb92023-01-24T18:21:16ZengUniversity of Darussalam GontorFountain of Informatics Journal2541-43132548-51132017-11-0122414510.21111/fij.v2i2.1067845Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5Indah Puji Astuti0Universitas Muhammadiyah Ponorogo<p class="BodyAbstract">The student is one of entities in University or Higher Education. The student has a variety of data, such as self-identity information such as address, type of school, work of parents, type of class, etc. In fact many students whose graduation rate is different, on time and not on time. The number of students who graduate is not on time will be a problem not only for university but also for faculty. The number of students graduating each year is one of points of assessment when faculty or study program submits accreditation. C4.5 Algorithm is one of classification algorithm with decision trees. In this study conducted an analysis of student data Engineering Studies Program University of Muhammadiyah Ponorogo 2012/2013. The decision trees in this case is useful for exploring student data, finding the hidden relationship between a number of candidate input attributes with a target attribute. The input attribute consist of, the type of school, address, work of parent, and type of class. The output attribute to classify is status, which consists of "on time" and "not on time". The results from this analysis shown that in this case the C4.5 algorithm can predict with an accuracy value only 82%.</p>https://ejournal.unida.gontor.ac.id/index.php/FIJ/article/view/1067algoritma c4.5student datadata miningdecision tree |
| spellingShingle | Indah Puji Astuti Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5 Fountain of Informatics Journal algoritma c4.5 student data data mining decision tree |
| title | Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5 |
| title_full | Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5 |
| title_fullStr | Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5 |
| title_full_unstemmed | Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5 |
| title_short | Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5 |
| title_sort | prediksi ketepatan waktu kelulusan dengan algoritma data mining c4 5 |
| topic | algoritma c4.5 student data data mining decision tree |
| url | https://ejournal.unida.gontor.ac.id/index.php/FIJ/article/view/1067 |
| work_keys_str_mv | AT indahpujiastuti prediksiketepatanwaktukelulusandenganalgoritmadataminingc45 |