Analisis Prediksi Nilai Akhir Mahasiswa Menggunakan Algoritma Regresi Linear Berbasis Machine Learning pada Program Studi Teknologi Informasi Universitas Bina Sarana Informatika: Penelitian

Khalisa Salsabila; Nahya Faulya Maulidia; Shabrina Auliya Zahra Hafid; Aisyah Shinta Balqis; Imam Budiawan; Desmulyati Desmulyati

doi:10.31004/jerkin.v4i3.4975

Authors

Khalisa Salsabila Universitas Bina Sarana Informatika
Nahya Faulya Maulidia Universitas Bina Sarana Informatika
Shabrina Auliya Zahra Hafid Universitas Bina Sarana Informatika
Aisyah Shinta Balqis Universitas Bina Sarana Informatika
Imam Budiawan Universitas Bina Sarana Informatika
Desmulyati Desmulyati Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.31004/jerkin.v4i3.4975

Keywords:

Machine Learning, Linear Regression, Final Grade Prediction, Attendance, Assignment Score

Abstract

The development of information technology in education demands a fast, objective, and data-driven academic evaluation system. Problems in higher education often involve lecturers' difficulty in monitoring and predicting student academic performance early, resulting in delayed response to declining performance. One solution that can be implemented is the use of Machine Learning. This study aims to analyze the prediction of students' final grades using a Machine Learning-based Linear Regression algorithm with attendance and assignment grades as variables. The case study was conducted on students of the Information Technology Study Program at Bina Sarana Informatika University using simulated data of 100 students, with the data divided into 80% training and 20% testing. Model evaluation used MSE, RMSE, and R². The results showed an R² value of 0.94, which means that 94% of the variation in students' final grades can be explained by attendance and assignment grades, while 6% is influenced by other factors. These findings indicate that the Linear Regression algorithm has excellent predictive performance in predicting students' final grades objectively and data-driven.

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