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Tarisno Amijoyo
Universitas Saintek Muhammadiyah
Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Physics Public Health Social Sciences Other

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Implementation Naïve Bayes Method To Prediction Of Student Achievement at Bimbel Sonai West Jakarta Amijoyo, Tarisno; Mumtaza, Amira
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 6 No. 2 (2023)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/inovatif.v6i2.505

Abstract

Education is a series of communication activities that have a purpose, between teachers and students, either directly or indirectly by utilizing other media to support the development of children as a whole. The purpose of this research was to classify in determining student achievement at Bimbel Sonai. To find out the results of the classification of student achievement, data mining methods are used. Classification with the Naive Bayes Algorithm. The research sample was obtained from 100 student, with simple random sampling technique. The attributes used are 4, namely Gender (C1), Average Value (C2), Parents' Economic Level (C3) and Parents' Education Level (C4). The results of the study showed that the accuracy value was 86.67%, class precision in the prediction of underachievement has a value of 75.00%, while the prediction of achievement has a value of 90.91%. Class recall for true underachievers has a value of 75.00%, while for true achievers it has a value of 90.91%. So with this analysis, it is hoped that it can help the institution, especially the Bimbel Sonai teacher in knowing student achievement in the teaching and learning process so that if it is known that there are many students who lack achievement, anticipation can be done in improving the quality of education in dealing with students who have less achievement so that it can produce generations and improve the quality of schools. Keywords : Data Mining, Naive Bayes, Student Achievement
Co-Authors Abdul Aziz Chaniago Abdul Halim Abdul Rachman Malik Alhambra Kevin Pasya Anton Yudhana Bernadisman, Dora Chaniago, Abdul Aziz Dimas Eko Prasetyo Dora Bernadisman Eryanti, Maisy Nur Ety, Indah Mus Fajar Buana, Fitrah Fakhri, Ahmad Fakhri HABIBAH NURFAUZIAH Hauzeni, Anita Imam Sagita Kurnia Kurnia Maisy Nur Eryanti Malik, Abdul Rachman Mel Siti Nurhaliza Meliana , Nina Meliana, Nina Mumtaza, Amira Najibah, Kholishotun Nasiruddin Ridwan, Nanang Rusydi Umar Sanjaya, Fery Shodiqqin, Adri Ahmad Shodiqqin Siti Asyaroh Yasmine, Annisaa Zakaria Arif Aditya