PENERAPAN ALGORITMA APRIORI UNTUK MENGIDENTIFIKASI LOKASI STRATEGIS PROMOSI SEKOLAH SWASTA - Sulistyo, Henny Wahyu; Hardian Oktavianto; Irawan, Dudi (Universitas Majalengka, 2025)
Schools must carry out effective promotions and target the right markets to attract prospective students efficiently. This study applies data mining using Association Rule and Apriori algorithms to uncover patterns for identifying promising promotional areas. It consists of four stages: data collection, preprocessing, implementation and testing, and evaluation, aiming to determine strategic locations for school promotion. The Apriori algorithm analyzed student data and produced 16 association rules, all with 100% confidence. Findings show that Kaliwates District appeared eight times, Sumbersari four times, and Tempurejo and Patrang twice each, indicating most students come from Kaliwates. The ‘Public Elementary School’ itemset appeared 12 times, revealing that most students enrolled from public rather than private schools. The study concludes that educational data plays a crucial role in shaping promotion strategies, especially through association analysis. Rules with the ‘District’ itemset in the antecedent are particularly useful as a promotional reference. These insights help decision-makers identify high-potential regions and school origins, supporting more targeted and effective promotional efforts.