E3S Web Conf.
Volume 31, 2018The 2nd International Conference on Energy, Environmental and Information System (ICENIS 2017)
|Number of page(s)||5|
|Section||11. Smart Information Systems|
|Published online||21 February 2018|
Prediction of Safety Stock Using Fuzzy Time Series (FTS) and Technology of Radio Frequency Identification (RFID) for Stock Control at Vendor Managed Inventory (VMI)
Master of Information System, Graduate School, Diponegoro University Semarang Indonesia
2 Department of Physics, Faculty of Science and Mathematics, Diponegoro University Semarang Indonesia.
3 Department of Information System, Faculty of Information Technology, Hasyim Asy’ari University, Jombang - Indonesia
* Corresponding author: email@example.com
This research was conducted by prediction of safety stock using Fuzzy Time Series (FTS) and technology of Radio Frequency Identification (RFID) for stock control at Vendor Managed Inventory (VMI). Well-controlled stock influenced company revenue and minimized cost. It discussed about information system of safety stock prediction developed through programming language of PHP. Input data consisted of demand got from automatic, online and real time acquisition using technology of RFID, then, sent to server and stored at online database. Furthermore, data of acquisition result was predicted by using algorithm of FTS applying universe of discourse defining and fuzzy sets determination. Fuzzy set result was continued to division process of universe of discourse in order to be to final step. Prediction result was displayed at information system dashboard developed. By using 60 data from demand data, prediction score was 450.331 and safety stock was 135.535. Prediction result was done by error deviation validation using Mean Square Percent Error of 15%. It proved that FTS was good enough in predicting demand and safety stock for stock control. For deeper analysis, researchers used data of demand and universe of discourse U varying at FTS to get various result based on test data used.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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