Analysis of Apriori Algorithm in Mining Drug Sales Data at Ridos Hospital
E S Ompusunggu1, S Efendi2, P H Putra3
1E S Ompusunggu, Student, Department of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Indonesia.
2S Efendi, Department of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Indonesia.
3P H Putra, Student, Department of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Indonesia.
Manuscript received on 09 May 2019 | Revised Manuscript received on 19 May 2019 | Manuscript Published on 23 May 2019 | PP: 1365-1367 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F12380476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study will apply the Apriori Algorithm in the field of health and the determination of drug purchase patterns. Data mining processing to find out what drugs are purchased by consumers, can be done with analytical techniques from consumer buying habits. The results of this study are: In this study the authors apply a priori algorithm using transaction data 20 on the 8th month transaction, resulting in 80% support value and confident 50% value. The result of applying the a priori method with a minimum support of 50% using 20 transaction data is if you buy abbotic medicine 500 mg, and buy a 14 terumo abocath, then buy astemizole. The application of a priori algorithm is based on the calculation of support and confidence values. in the process of calculating the support and confidence values it will be more difficult, if the data you want to process is large. The a priori method used is quite effective in providing the final combination of drugs that are often purchased by consumers. The level of accuracy of testing using a priori method is 96%.
Keywords: Data Algorithm Mining Analysis Method Application Processing.
Scope of the Article: Data Mining