Pembinaan indeks jenayah curi kenderaan dengan pendekatan berbilang kriterium dalam persekitaran kabur

• Auteur principal: Mohd.firdaus, Abd Khabir
• Format: Thèse
• Langue: anglais
• Publié: 2022
• Sujets: QA299.6-433 Analysis; QA76.76 Fuzzy System.
• Accès en ligne: https://etd.uum.edu.my/10233/1/s900144_01.pdf

An index is a measure of the performance of a situation that displays the value of the final score resulting from a combination of several criteria values mathematically. The existing index of vehicle theft is built on the assumption that all criteria are equally important and based on numerical data only without considering ambiguity aspect, particularly the causes of the crime. Moreover, there was no decision-makers involvement to assess the level of contribution of criminal criteria based on their knowledge and experience. Therefore, this study developed an improved InJeCK by considering the fuzziness. InJeCK also involves decision-makers in determining the degree of importance of vehicle theft crime criteria, in addition to numerical data analysis obtained from related agencies. The subjective weights in this study utilized Z-numbers through the level of contribution of the criteria evaluated in the representation of two triangular fuzzy numbers. Objective weights used the degree of uncertainty through entropy measurements. These two weights were aggregated to form an aggregated weight that balances the weaknesses of both subjective and objective weights. Next, InJeCK was computed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank 82 areas in Peninsular Malaysia. InJeCK values were visualized using color maps to be more informative. The results show that the criteria of car theft, higher education and unemployment are the three most influential criteria in vehicle theft crime based on the aggregated weights. The InJeCK values show that Kuala Lumpur is the riskiest area for vehicle theft cases. This study has contributed to the field of multi-criteria decision-making by considering fuzzy environment in the development of vehicle theft crime index. Besides, the findings of the study can also assist those involved in curbing vehicle theft in particular and property crime in general.