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Handling documents using information technology have been applied in more than decades. It can save paper, speed up communications, save time and increase productivity of work. It is important because there is much valuable information in the form of documents such as books, letters, minutes of meeting, rules and regulations memo that support the programme accreditation process. However, the current practice is still using the traditional file system. This is very challenging for document search process, particularly during the audit process. The major purpose of this paper is to indicate that electronic document management technology can truly support in managing document evidences. This scenario leads towards the development of an integrated document management for academic quality assurance system (iDMQA). iDMQA is certainly useful in reducing the duplication of document evidences that occurs with the current system. Still, this system can be enhanced, especially in terms of tracking the history of document uploads.

<span>This paper presents the optimization of house purchase recommendation system (HRPS) using Genetic Algorithm.  Everyone in this world has their own dream house and plan to purchase it depending on their budget and based on the house preferences. Homebuyers face problem in comparing the house property websites according to the factors during the house survey. Subsequently, it is time-consuming in making the decision and they need to bear the transportation cost as they will need to travel to one house developer office to another. In addition, some of the homebuyers felt disappointed when their expectations were not met. Thus, in order to optimize the preferences, in this paper, we present a web-based house purchase recommendation system (HPRS) using a genetic algorithm. Then, it follows by test the functionality and usability of the system. As a result, the system found to function accordingly and obtain more than the average score of system usability scale testing. For further research, it is recommended to add more data to the database and compare with other algorithms.</span>