SCHOLAR AI: INNOVATION IN SCHOLARSHIP SELECTION CLUSTERING BASED ELIGIBILITY CLASSIFICATION BASED ON MACHINE LEARNING - Tutik Lestari; Achmad Farouq Abdullah; Oddy Virgantara Putra; Onno Widodo Purbo (LPPM Nusa Mandiri, 2026)
Scholarship allocation is a crucial process that ensures financial support for students based on academic performance, potential, and financial need. However, the scholarship selection process at Pondok Pesantren Darunnajah has faced challenges in capturing the holistic characteristics of applicants. This research proposes a machine learning model that integrates clustering and predictive techniques to improve the scholarship selection process. The dataset consists of 300 student samples with attributes such as academic scores, tahfidz (Qur'an memorization), family income, and extracurricular activities. These features help determine if a student qualifies for one of three scholarship schemes: Beasiswa Tahfidz, Beasiswa Prestasi, or Beasiswa Ashabunnajah, or if they are deemed