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September 10, 2025JUITA Jurnal InformatikaOpen Access

Course Scheduling Using Genetic Algorithms Enhanced by Linear Regression for Data Mining Course Participants

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Authors

AUArie Susetio UtamiAMAgust Isa MartinusFWFreddy Wicaksono

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Overview

This research demonstrates an innovative course scheduling system using genetic algorithms and linear regression for predicting participant numbers.

Key Points

  • The scheduling system minimizes conflicts to 0 percent by optimizing course schedules with advanced algorithms.
  • High prediction accuracy was achieved with a coefficient of determination over 95% and RMSE below 10.
  • Genetic algorithms were employed with a fitness function to effectively manage class and instructor conflicts.
  • The approach utilized linear regression to predict future participant numbers based on historical data from 2019 to 2022.

Cite This Study

Utami et al. (2025) studied this question.

synapsesocial.com/papers/68c1c9dd54b1d3bfb60f3107https://doi.org/10.30595/juita.v13i2.25598
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