PREDIKSI DIABETES: ANALISIS KOMPREHENSIF DENGAN KLASIFIKASI NAÏVE BAYES DAN INTEGRASI RAPIDMINER - Muttaqin, Aji; Wahyuni, Tantri (SEMINAR TEKNOLOGI MAJALENGKA (STIMA), 2025)
This research explores diabetes prediction using a classification method by applying the Naive Bayes algorithm and utilizing the RapidMiner application. Using a clinical dataset that includes parameters such as glucose levels, body mass index, and blood pressure, a predictive model was developed and evaluated with an efficient data processing approach via RapidMiner. Experiments show that this model provides accurate predictions regarding diabetes risk. These findings can support the implementation of practical solutions in the early diagnosis of diabetes.