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All Journal Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research
Fauzia Rahmadani, Noni
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Humanities Economics, Econometrics & Finance Education Social Sciences Other

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Prediksi Nilai Mahasiswa Berdasarkan Riwayat Akademik Menggunakan Jaringan Syaraf Tiruan Fauzia Rahmadani, Noni; Nugroho, Agung; Sofinah Haharap, Lailan
Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 2 No. 1 (2025): NOVEMBER 2024 - JANUARI 2025
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v2i1.2327

Abstract

Predicting students' academic performance is crucial in enhancing the quality of education in higher institutions. This study aims to develop a model for predicting student grades based on academic history using Artificial Neural Networks (ANN) with the backpropagation method. Academic data and supporting variables from students are used as inputs in the model, which aims to forecast future academic achievements. In this research, the ANN was structured with a layered architecture consisting of 5 neurons in the input layer, one hidden layer with 7 neurons, and an output layer. The model was trained using the backpropagation algorithm to minimize Mean Square Error (MSE) and improve prediction accuracy. Testing results show that the ANN model achieved convergence with an MSE value of 0.01363 in 68 epochs. Based on these findings, the developed model can be utilized by academic advisors to monitor and predict students' academic progress. Overall, this research contributes to providing an effective data-driven tool for academic mentoring processes, supporting higher education institutions in optimizing students' potential for achieving maximal academic success.
Co-Authors Nugroho, Agung Sofinah Haharap, Lailan