Main Article Content
Abstract
Aim of this research is to apply Neural Network Algorithm to predict score of mathematic in the national exam. During the time, the teacher only provided national exam materials and additional tryout tests without knowing how to predict the exam scores in mathematics subject. Data mining neural network algorithm obtained \Root Mean Square Error (RMSE) values which were used as basic improvement and clustering class By conducting research using data mining neural network algorithm, it proved that this model can be used to predict scores of Mathematics subject at SMK Negeri 1 Pakis Aji.. The result of this research by using data mining neural network algorithm found RMSE 0138 +/- 0.092. The lower the RMSE values the more accurate the neural network to predict mathematics scores of SMK Negeri 1 Pakis Aji.
Received: 18 Agustus 2019; Accepted: 5 Januari 2020; Published: 14 January 2020
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References
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References
Samsuri, Prediksi Nilai Ujian Nasional Pada Sekolah Menengah Kejuruan Dengan Metode Neural Network. Teknik Komputer Dan Jaringan(Tkj) Sekolah Menengah Kejuruan (SMKN 3) Palu, Dinas Pendidikan Palu (2013).
D.T. Larose, Discovering Knowledge in Data: An Introduction to Data Mining, Wiley2005.
I.H. Witten, E. Frank, Data mining: practical machine learning tools and techniques with Java implementations, Acm Sigmod Record 31(1) (2002) 76-77.
J.S.D. Raharjo, Model Artificial neural network berbasis Particle swarm optimization untuk Prediksi laju inflasi, Jurnal Sistem Komputer 3(1) (2013) 10-21.
D.K.D. Susanto, M. Bettiza, N. Nikentari, Prediksi Nilai Uas Siswa Smk Menggunakan Algoritma Levenberg-Marquardt, (2015).
D. Aprilla, D.A. Baskoro, L. Ambarwati, I.W.S. Wicaksana, Belajar data mining dengan rapidminer, Jakarta: Gramedia Pustaka Utama (2013).
W. Utomo, Prediksi nilai ujian nasional produktif sekolah menengah kejuruan menggunakan metode Neural Network, Techno. Com 14(1) (2015) 33-41.
Sugiyono, Metode penelitian pendidikan:(pendekatan kuantitatif, kualitatif dan R & D), Alfabeta2008.
P.V.V. Theja, L. Vanajakshi, Short term prediction of traffic parameters using support vector machines technique, IEEE, 2010, pp. 70-75.
X. Wu, V. Kumar, The top ten algorithms in data mining, CRC press2009.
E. Prasetyo, Data Mining konsep dan Aplikasi menggunakan MATLAB, Yogyakarta: Andi (2012).