The Implementation of Data Mining for Association Patterns Determination Using Temporal Association Methods in Medicine Data

Clinic is one of the businesses that perform health services for people in the surrounding environment. The clinic also provides medicines that will be given to patients who conduct health checks. The problem that occurs in these clinics is that the medicine data recap is only using excel data, the purchase of medicine stocks that are conducted only based on medicine that out of stock. Based on an interview with one of the nurse at a clinic on Yogyakarta site, occassionally, there are a case that a surge of patient that running out medicine supplies, while on the other hand there are lots of medicine accumulation occurred because these medicines was not needed by the patient. This is because the clinic has not been able to predict the medicine that are often issued by the clinic. Therefore, this research aims to build a data mining program with the Temporal Association Rules method for determining the relationship between medicines which is accompanied by the date of release of the medicine.The method used in this research is Temporal Association Rules with the Apriori Algorithm to find association rules that meet the support and confidence limits, and in the testing process lift ratio is used.The results of this research are applications that able to provide information on patterns of medicine data associations and the date of medicine's release. The test results with 8186 amount of data and support value 50% and confident value 70% with lift values above 0, the patterns of association rules obtained is 6.