International Journal of Informatics and Communication Technology (IJ-ICT) Vol. 3, No. 3, October 2014, pp. 171~177 ISSN: 2252-8776  171 Journal homepage: http://iaesjournal.com/online/index.php/IJICT Decision Support System using Data Mining Method for a Cross Selling Strategy in Retail Stores Imam Tahyudin, Mohammad Imron, Siti Alvi Solikhatin Departmen of Information System, STMIK AMIKOM Purwokerto Article Info ABSTRACT Article history: Received Jul 18, 2014 Revised Sep 21, 2014 Accepted Sepg 22, 2014 A sales transaction dataof a retail company which is collect edevery day is enormous. Very large data will bemore meaning fultoin crease the company’s profitsif itcanbe extracted properly. Based on the research resultsof Andhika, et al[1], ZhangandRuan[6], Herera et al [7], Witten [11], explained that one of the methods that can gather information from the transaction data is the method of association. With this method it can be determined the patterns of transactions performed simultaneously and repeatedly. Thus, it can be obtained amodel that can be used as a reference for cross selling sales strategy. The purpose of this research is to apply data mining association methods of data mining by using apriori algorithm to create a new sales strategy for cross selling. Based on calculations, Association Rule is implemented by applying Confidence value=0.8while the value of Support=0.1 of the defined minimum value, the total result are 77 rules. Keyword: Apriori algorithm Association Cross selling Data mining Retail stores Copyright © 2014 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Imam Tahyudin Departmen of Information System STMIK AMIKOM Purwokerto Purwokerto, Indonesia. Email: imam.tahyudin@amikompurwokerto.ac.id 1. INTRODUCTION Decision Support System (DSS) began to attract attention among programmers and systems analysts. These systems assist decision-making by managing data and using certain models to solve the problem. Decisionsupport systems to be special because it is able tosolv ethe problem of un structured or semi-structured. In many areas, a decision support system has many perceived benefits and dependency to use the system in creasing with the increasing complexity of the data management proces seach information system. Application of the DSS to a business interest plays a very important role, such as to provide advice in the preparation of cross-selling strategy atretail stores. One method that can be used to solve the seproblemsis by using association method of apriori algorithms. The study on the application of the method of Apriori Association has been done by previous studies with a variety of objects. Research conducted by Andhika et al [1] entitled Excavation Association Patterns in Data Warehouse Agent Manufacturing Using Microsoft SQL Server (Case Study: PTXYZ) aimstocreatean integrated system, using the data warehouse and association method of rule mining, that found a pattern of sales transaction data from previous periods regarding the relationship between-a variable that is knowntendency of the product to be purchased by the customer in conjunction with the specific product. The method used is the design ofthe data, starting from the formulation of the problems encountered, and then do a search the required data. Once collected, the data is filtered and transformed that into a form consistent database. Further more, applying association rule mining using Microsoft Visual Studio. The end result is an