E3S Web Conf.
Volume 73, 2018The 3rd International Conference on Energy, Environmental and Information System (ICENIS 2018)
|Number of page(s)||6|
|Section||System Information and Decision Support System|
|Published online||21 December 2018|
Information System Prediction With Weighted Moving Average (WMA) Method And Optimization Distribution Using Vehicles Routing Problem (VRP) Model for Batik Product
1 Magister of Information System, School of Postgraduate Studies, Diponegoro University, Semarang - Indonesia
2 Department of Physics, Faculty of Sains and Mathematic, Diponegoro University, Semarang - Indonesia
* Corresponding author: email@example.com
Distributing the products evenly to the customers is the problem faced by the producer of batik product. The purpose of this research is to optimize product distribution using demand prediction data from each store. The way of distributing products affects products brand and revenue in society. To cover this problem we propose the method to fulfil customers demand and to promote the brand by using Weighted Moving Average (WMA) to forecast product demand in each distributor store. To deliver the product for the customer, we are using the model of Vehicle Routing Problem (VRP) and Sequential Insertion Algorithm. We obtained the result that both distribution cost and travel time of distribution is successfully reduced. The results obtained that the WMA method can predict product demand by generate the small error value with MAPE the result is 0 until 17% which classified as very accurate-good. For distribution optimization using the VRP model and Sequential Insertion algorithms the result of optimal costs is IDR 36244, with a previous cost is IDR 150.000 in one month so can reduce 75%. Besides that, the travel time is 130.05 minutes with the distance 69.7 km, and routes that have been optimized.
Key words: batik product / distribution / optimization / weighted moving average (WMA) / vehicle routing problem (VRP) / algorithm sequential insertion
© The Authors, published by EDP Sciences, 2018
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