IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI DALAM MENENTUKAN PERSEDIAAN OBAT - Gesta Wulandari; Sasmita Sasmita; Fitria Rahmadayanti (Politeknik Bisnis Indonesia, 2024)
This study aims to enhance the efficiency of drug inventory management at UPTD Puskesmas Rawat Inap Bandar Kota Pagar Alam by applying the Apriori algorithm to analyze patient drug purchasing patterns. The dataset consists of 470 drug transactions from January to May 2023, with a minimum support of 12% and a minimum confidence of 10%. The research follows the CRISP-DM method, which includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Analysis using RapidMiner revealed several association patterns, such as patients who purchase ibuprofen 400 mg also tend to buy calcium lactate 500 mg with a confidence of 0.100, and patients who buy sanmol 500 mg also buy pyrantel pamoate tab scored 125 mg with a confidence of 0.122. Implementing this algorithm helps the health center manage drug inventory more effectively, reducing overstock and understock issues, and minimizing errors in drug data recording. The study concludes that the application of the Apriori algorithm is beneficial for identifying drug purchasing patterns, thereby improving the quality of healthcare services at the health center.