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  • 标题:Classification of Metacognitive into Two Catagories to Support the Learning Process
  • 本地全文:下载
  • 作者:Husnul Rahmawati Sakinnah ; Adhistya Erna Permanasari ; Indah Soesanti
  • 期刊名称:Jurnal Pendidikan Sains (JPS)
  • 印刷版ISSN:2442-3904
  • 出版年度:2017
  • 卷号:5
  • 期号:1
  • 页码:11-16
  • DOI:10.17977/jps.v5i1.9069
  • 出版社:Pascasarjana Universitas Negeri Malang (UM)
  • 摘要:Learning outcomes are the patterns of actions, values, understanding, attitudes, appreciation and skills. Learning outcomes are related to the metacognitive of student where the elements contained in metacognitive is cognitive. The relationship between cognitive and metacognitive which is the foundation of cognitive is metacognitive. There are two components such as knowledge of metacognitive and regulation of metacognitive. In the learning process, cognitive factors are not the only one that can support, but also a metacognitive factor is a very influential factor for the success of the learning process. Thus, it is very important to do with a deeper analysis about metacognitive by identifying metacognitive level to support the learning process. Identification of metacognitive is performed by using Naïve Bayes Classifier algorithm (NBC) which NBC is one of an algorithm that is used for classification algorithm for data mining. In these studies, it is obtained that the accuracy scored 88,0597% when tested using NBC.
  • 其他摘要:Abstract : Learning outcomes are the patterns of actions, values, understanding, attitudes, appreciation and skills. Learning outcomes are related to the metacognitive of student where the elements contained in metacognitive is cognitive. The relationship between cognitive and metacognitive which is the foundation of cognitive is metacognitive. There are two components such as knowledge of metacognitive and regulation of metacognitive. In the learning process, cognitive factors are not the only one that can support, but also a metacognitive factor is a very influential factor for the success of the learning process. Thus, it is very important to do with a deeper analysis about metacognitive by identifying me-tacognitive level to support the learning process. Identification of metacognitive is performed by using Naïve Bayes Classifier algorithm (NBC) which NBC is one of an algorithm that is used for classification algorithm for data mining. In these studies, it is obtained that the accuracy scored 88,0597% when tested using NBC. Key Words : metacognitive, knowledge of metacognitive, regulation of metacognitive, cognitive, Naïve Bayes Classifier (NBC)   Abstrak : Hasil pembelajaran merupakan pola tindakan, nilai-nilai, pemahaman, sikap, apresiasi dan keterampilan. hasil belajar terkait dengan metakognitif siswa di mana unsur-unsur yang terkandung dalam metakognitif adalah kognitif. Hubungan antara kognitif dan metakognitif merupakan dasar dari kognitif adalah metakognitif. Terdapat dua komponen dalam pengetahuan metakognitif dan regulasi metakognitif. Dalam proses pembelajaran, faktor kognitif bukan satu-satunya yang dapat mendukung, tetapi juga faktor metakognitif adalah faktor yang sangat berpengaruh bagi keberhasilan proses pembelajaran. Jadi, sangat penting untuk melakukan analisis yang lebih mendalam tentang metakognitif dengan mengidentifikasi tingkat metakognitif untuk mendukung proses pembelajaran. Identifikasi metakognitif dilakukan dengan menggunakan algoritma Naïve Bayes Classifier (NBC) dimana NBC merupakan salah satu algoritma yang digunakan untuk algoritma klasifikasi untuk data mining. Dalam penelitian tersebut diperoleh bahwa nilai akurasi adalah 88,0597% saat diuji menggunakan NBC. Kata kunci : Metakognitif, Pengetahuan Metakognitif, Peraturan Metakognitif, Kognitif, Naïve Bayes Classifier (NBC)
  • 关键词:metacognitive;knowledge of metacognitive;regulation of metacognitive;cognitive;Naïve Bayes Classifier (NBC)
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