Abstract
The use of a crime dashboard is important as it should be widely spread for citizens to understand and track crime trends in Malaysia. There is currently a lack of interactive dashboards about crime rates in Malaysia for Malaysian citizens. The Department of Statistics Malaysia (DOSM) only provided read-only files and out-of-date information available for everyone to use. The dashboard should integrate data visualization, forecasts, and educational materials to provide Malaysian residents with a better understanding of the situation. This article focuses on the steps involved in constructing a CrackDown interactive data visualization dashboard. This research will benefit its stakeholders such as Malaysian citizens, Royal Malaysia Police (RMP), and researchers. The aim is to create an interactive dashboard for Crackdown using a combination of Agile and OSEMN methodology, with visualization and relevant information. The design of the dashboard uses feature visualization, and related articles that are educational for the user. The research also applied the data design process which involved the extract, transform, and load (ETL) and helped in obtaining a good data quality. Based on the findings, despite a decrease in crime patterns from 2017 to 2022, there are still concerns among citizens. Selangor was the state with the highest crime cases followed by Kuala Lumpur, Johor, Sarawak, and Kedah. Meanwhile, the most frequent crimes in Malaysia are motorcycle theft, followed by stealing, home breaking, car theft, and unarmed bandits. From the result, Crackdown intends to enable Malaysian citizens to track crime rates in Malaysia based on different categories and raise awareness and knowledge of crime prevention and guidance for a more secure future.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Mahadi, Maisarah Ros UNSPECIFIED Abd Karim, Norisan UNSPECIFIED GS, Jasber Kaur UNSPECIFIED Redzuan, Fauziah UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Electronic digital computers |
Divisions: | Universiti Teknologi MARA, Selangor > Puncak Perdana Campus > Faculty of Information Management |
Journal or Publication Title: | Journal of Information and Knowledge Management (JIKM) |
UiTM Journal Collections: | UiTM Journal > International Journal of Information and Knowledge Management (JIKM) |
ISSN: | ISSN:2231-8836 ; E-ISSN:2289-5337 |
Volume: | 2 |
Page Range: | pp. 143-155 |
Keywords: | Crime, data visualization, forecast, knowledge management. |
Date: | November 2023 |
URI: | https://ir.uitm.edu.my/id/eprint/87362 |