Fuzzy Tsukamoto based Decision Support Model for Purchase Decision in Pharmacy Company 
Guroh Kharisma Ramadhan1, Ditdit Nugeraha Utama2
1Guroh Kharisma Ramadhan, Department of Computer Science, BINUS Graduate Program – Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia.
2Ditdit Nugeraha Utama, Department of Computer Science, BINUS Graduate Program – Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia.
Manuscript received on November 10, 2019. | Revised Manuscript received on November 17, 2019. | Manuscript published on 30 November, 2019. | PP: 3868-3874 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8243118419/2019©BEIESP | DOI: 10.35940/ijrte.D8243.118419
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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: The difficulty in determining a number of item purchased is one of essential activities in inventory management. This study scientifically proposes a decision support model to decide how much number of next item purchased by a pharmacy company. The main objective of the developed model is to control a minimum stock at a certain time and condition and support in making the decision on how many items should be purchased at next time. Decision support model considers two independent parameters; lead time and stock. Tsukamoto’s fuzzy system is functioned in this study to avoid blurring parameter values from someone making a decision. Each criterion is divided into three membership functions; with nine fuzzy-rules used. The model also supports changing parameters if parameter values are changed. Based on the results of model test done, the optimized number of item purchased at the Pharmacy Company is able to be proposed practically.
Keywords: Inventory Management, Purchase, Fuzzy Logic, Tsukamoto, Pharmacy.
Scope of the Article: Fuzzy Logic.