EKSAKTA: Journal of Sciences and Data Analysis
VOLUME 1, ISSUE 1, February 2020

Neural Network Model for Mathematic Scores Prediction: Case Study in SMK Negeri Pakis Aji, Jepara, Indonesia

Adi Sucipto (Program Study Teknik Informatika, FST, Universitas Islam Nahdlatul Ulama Jepara)
Joko Minardi (Program Study Sistem Informasi, FST, Universitas Islam Nahdlatul Ulama Jepara)



Article Info

Publish Date
17 Jan 2020

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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Journal Info

Abbrev

eksakta

Publisher

Subject

Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology

Description

Ekstakta is an interdisciplinary journal with the scope of mathematics and natural sciences that is published by Fakultas MIPA Universitas Islam Indonesia. All submitted papers should describe original, innovatory research, and modelling research indicating their basic idea for potential ...