A Decision Support System Using Demographic
Issues: A Case Study in Turkey
Suat Secgin
and Gokhan Dalkilic
Department of Computer Engineering Department, Dokuz Eylul
University, Turkey
Abstract: The demographic distribution of people by cities is an important parameter to address the people’s behaviour. To distinguish people behaviour is useful for companies to understand the customer behaviour. In this article, a case study covering all 81 cities in Turkey and measuring 35 topics for each of them is handled. By using these topics and cities, it is investigated that how the cities are clustered. Because its efficiency, the Agglomerative hierarchical clustering and the K-medoids clustering methods in rapidminer data mining software are used to cluster the data. To measure the efficiency of the agglomerative clustering algorithm, the Cophenetic Correlation Coefficient (CPCC) is used. After clustering, the results are inserted into a geographic information system to depict the results in a Turkey map. The results show that, the cities distributed in the same geographical areas are in the same clusters with some exempts. On the other hand, some cities those are in different provinces show the same behaviour. The results of the study can also be used as a decision support system for a customer relations management.
Keywords:
Agglomerative clustering, customer behaviour, data mining, decision support.
Revived July 24, 2014; accepted August 16, 2015