PENGEMBANGAN APLIKASI PENGENDALIAN PERSEDIAAN OBAT DI APOTEK MENGGUNAKAN METODE HYBRID PERIODIC ORDER QUANTITY - MOVING AVERAGE

Abstract

A pharmacy is a place of health service but indirectly also an effort to get the benefit. From the business point of view, of course, the pharmacy requires a system of processing inventory of goods, especially drugs - drugs in order to avoid losses. One of the pharmacies that have not optimally utilized the technology is at Apotek Karunia Asih located in Canggu Badung Bali. To overcome the problem of inventory control, at Apotek Karunia Asih requires inventory control application. The purpose of this research is to develop inventory control application with hybrid periodic order quantity - moving average method in Apotek Karunia Asih which gives benefit to the controlling of goods in pharmacies so that the goods and drugs sold in another are no longer past the expiration date, dead stock, stacking or stock shortages. Development of inventory control application with hybrid periodic order quantity - moving average method in Apotek Karunia Asih uses SDLC (Software Development Life Cycle) process to describe the stages in software development. SDLC process used is waterfall model. Waterfall model is a model that is systematic and sequential in building software, starting from the analysis, design, coding, testing, and support or maintenance. Implementation of this research is applied by using PHP programming language with the help of Codeigniter framework. For the testing process, five (5) test process stages are performed: (1) white box test which states that the source code implementation is appropriate and there is no error, (2) black box test to find out whether all software functional is appropriate, (3) test the suitability of the system to find out the correctness of the calculation process performed by the application, (4) the user response test which states the application and the methods used are very appropriate in controlling the supply of drugs in pharmacies; (5) the previous training test on forecasting that the previous training score will be used to predict the need is 6 because it has the smallest MAPE and MSE so that the forecasting results can be in accordance with the actual data.