PENERAPAN DATA MINING DENGAN ALGORITMA NAÏVE BAYES UNTUK ANALISIS KEBUTUHAN STOK OBAT DI KLINIK IDAMAN AS'ADIYAH SUKOREJO - Muchammad Atfal Nur Afil; Zaehol Fatah (Jurnal Ilmiah Multidisiplin Ilmu, 2024)
Medicine stocks that are not well managed can cause shortages or excess stocks which have an impact on health services in clinics. This research aims to apply the Naïve Bayes algorithm to analyze drug stock needs at the Idaman As'adiyah Sukorejo Clinic. By using historical data on drug sales and monthly demand for one year, the Naïve Bayes algorithm is used to predict the type of drug that will be needed in the following month. The research results show that this algorithm is able to predict drug stock needs with an accuracy of up to 85%, which can help clinic managers plan the purchase and distribution of drugs more efficiently.