Crowd processing price comparison application with rule based system / Hairulnizam Ghazali

• Main Author: Ghazali, Hairulnizam
• Format: Student Project
• Language: English
• Published: Faculty of Computer and Mathematical Sciences 2015
• Online Access: http://ir.uitm.edu.my/id/eprint/17666/2/PPb_HAIRULNIZAM%20GHAZALI%20CS%2015_5.pdf; http://ir.uitm.edu.my/id/eprint/17666/
• Institution: Universiti Teknologi Mara

Online shopping has become increasingly popular, due to fact that the prices are lower than conventional shopping and also it is convenience without physically doing it. Malaysia is experiencing the crux of cost of living that troubled consumers this year, and since the government rolls back its system of subsidies, Malaysians may struggle with debts. In modern countries such us United States and United price of goods, but the technology itself only applicable in their domain. In Malaysia, the government had introduced 1 Pengguna, an online portal for prices checker among several hypermarkets. 1 Pengguna provides users with set of price database of certain goods that can be retrieved from their portal, however, the implementations and service offers are still in the beta stages. This project may help consumers to find cheapest product they desired aims at a selected area by using their smartphone in Malaysia. One of the biggest problems when dealing with price comparison is that the price in not up to date with the current price listed. This problem due the fact that database is maintained by each hypermarket and thousands of items keep changing their price every day, making the application hard to get the latest price. Therefore, this mobile app will use the power of crowdsourcing to get some data and use rule-based system to determine the cheapest price for selected products. Based on the finding, it has shown that it can help consumer to find affordable prices by using the rule-based system. It also may help the marketing organizations to cater customer needs and create profitable revenue by enhancing the margin of preferable products selected by customers. Further studies with more focus on Crowd Processing method and Geo-location based on the GPS therefore is highly suggested.