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All Journal EKSAKTA: Journal of Sciences and Data Analysis
Joko Minardi
Program Study Sistem Informasi, FST, Universitas Islam Nahdlatul Ulama Jepara
Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology

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Neural Network Model for Mathematic Scores Prediction: Case Study in SMK Negeri Pakis Aji, Jepara, Indonesia Adi Sucipto; Joko Minardi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 1, ISSUE 1, February 2020
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol1.iss1.art5

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
Co-Authors A.A. Ketut Agung Cahyawan W