Large Language Models (LLMs) have recently demonstrated remarkable capabilities across a wide range of domains, including education, programming, and scientific problem-solving. However, mathematical problem-solving remains challenging because LLMs often generate logically inconsistent solutions and are susceptible to...
Imam Fadhkur Rokhim, Diana Purwitasari, R. Anggraini et al.· Engineering, Technology &...· 0 citations
Predicting student dropout in higher education is challenging due to class imbalance and class overlap, particularly in multiclass classification. This study presents a hybrid method that combines weight-based oversampling and energy-based cleaning to address class imbalance and class overlap. The method generates synt...
Rahmad Hidayat, Diana Purwitasari, Ahmad Saikhu et al.· Engineering, Technology &...· 0 citations
Loan approval prediction remains a critical yet challenging task in financial risk management, particularly due to class imbalance and variability across lending datasets. This study presents a comparative evaluation of eleven machine learning and ensemble learning algorithms for loan approval prediction, evaluated acr...
Ilham Putra Ariatama, Wahyudi Setiawan, A. Amirullah et al.· Jurnal Teknik Informatika (J...· 0 citations
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