Construction of Vehicle Theft Index by Using TOPSIS Method with Entropy Based Criteria Weights

Abstract

Property theft especially vehicle theft is a major contribution of entire crime. Estimating the level of crime by depending solely on the total of vehicle theft cases recorded is insufficient in order to observe the direction of the problem itself. The aim of this paper is to construct a vehicle theft index based on multi-criteria decision method to analyse vehicle theft pattern in particular and property theft in general for 82 areas in peninsular Malaysia. As vehicle theft is the major part of property crime, it is influenced by other criteria such as unemployment, level of education, immigrant and drug which should be considered in the vehicle theft index construction. Hence, this study takes into account the diversity of intrinsic of information in the criteria by measuring the entropy or the degree of diverseness of the data as proxies of the relative importance of the criteria.  Then a Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) was used to construct the vehicle theft index of 82 areas in peninsular Malaysia. The finding shows the top three areas in descending order are Kuala Lumpur, Petaling and Johor Bahru. The vehicle theft index constructed in this study can illustrate the actual direction of theft problem in Malaysia and the index construction process can be applied in other countries as well.