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Journal : Jurnal Penelitian Pembelajaran Fisika

Analisis dan Pemetaan Mata Kuliah Bersyarat Program Studi Fisika Menggunakan BackPropagation Neural Network Eva Gusmira; Muhammad Kukuh; Arif Ma'rufi
Jurnal Penelitian Pembelajaran Fisika Vol 13, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jp2f.v13i2.12979

Abstract

This study aims to analyze and map the conditional courses at the Tadris Physics Study Program, Faculty of Tarbiyah and Teacher Training, Sulthan Thaha Saifuddin State Islamic University Jambi. This research is an applied science research, data analysis using quantitative descriptive technique. The data is in the form of documenting the value of the 2019/2020 Tadris Physics Study Program students. The research sample consisted of 11 sample subjects from 19 population subjects. The data is processed using Backpropagation Neural Network with Python programming language. Validation and accuracy of prediction results using Mean Absolute Percentage Error and determinant coefficient R Square. The prediction results of conditional courses obtained are accurate and valid with MAPE values <10% (very good) and R Square values close to 1. This study shows that the mapping of prerequisite courses set by the study program is appropriate, except for Basic Physics Courses. 2 (R 0.216) and Mathematics Physics Course I (R 0.50) require additional other prerequisite courses.Keywords: mapping; conditional courses, backpropagation neural network