Flood is the major natural hazard in Malaysia in terms of populations affected, area extent, frequency, social–economic damage, and flood duration. This shows the importance of providing comprehensive and effective flood mitigation management, which requires government agencies to enhance their employment performance that involves technological innovation. A flood early warning and response system (FEWRS) is essential to ensure that all stakeholders receive the right information and are provided with necessary actions and response information to avoid loss of lives and property. It should have some effective usability features and success components of its strategic information access and display; existing FEWRS fail and often do not effectively provide information on flood disasters to reduce their impacts at a local level to save the population’s lives. The measurement of information system (IS) success remains a top concern for researchers, managers, and practitioners. Therefore, this study seeks to provide a systematic overview of the most successful model of employment-related technical advancement for the management of flood disasters to improve its employees’ performance. In addition, examined factors that affect the successful implementation of flood management approaches, based on a systematic literature review among IS, show interrelationship of success factors. Findings from the literature suggest that the DeLone and McLean (D&M) model is the most widely employed model, recorded in 28 studies (39%). Further description of the 28 studies indicates that the D&M was either adopted alone or integrated with other theories. Moreover, results suggest the D&M is has been applied alone 39% of the time and has been extended 29% of the time; in total, 68% of the time, D&M has been applied either alone or extended in the information system domain. Additionally, 22% of the time it has been integrated with other theories.
The traditional banking system, such as transactions over the counter using bank book is enhanced by adding the elements of electronic banking, where nowadays all transaction can be done over the network, because of globalization and the advancement of information and communication technology. However, significant threats to this technology also come in parallel, such as from banking frauds. This is why building trust among banking users by providing security mechanisms is very important. In the electronic banking, security mechanisms mainly focus on proving a secure environment for the online transaction, especially user authentication. Many researchers have been proposed various models for the online user access authentication for the banking industry. Most of the researches are based on traditional the form of username and password, but with the varying mechanism of password forms. For example, password in arbitrary value, password in arbitrary value through secured channel, as well as biometric like fingerprint recognition, voice recognition, or retina recognition. In this paper we reviewed the current existing user access for online banking based on mobile phone, the functions of the SIM card, the characteristics mobile of the SIM card are described. Cloning, a threat to the SIM card is also described. Findings show that all the security model for online user access contains password in the form of value, biometric, or PIN. Thus, none of the existing user access proposed the idea of the user access based on International Mobile Equipment Identity (IMEI) number to strength the security of the user access. The IMEI is a 15- or 17-digit code that uniquely identifies mobile phone sets.
Identifying which biodiversity species are more dominant than others in any area is a very challenging task. This is because of the abundant of biodiversity species that may become the majority species in any particular region. This situation create a large dataset with a complex variables to be analysed. Moreover, the responds of organisms and environmental factors are occurred in a non-linear correlation. The effort to do so is really important in order to conserve the biodiversity of nature. To understand the complex relationships that exist between species distribution and their habitat, we analysed the interactions among bird diversity, spatial distribution and land use types at Kenyir landscape in Terengganu, Malaysia by using artificial neural network (ANN) method of self-organizing map (SOM) analysis. SOM performs an unsupervised and non-linear analysis on a complex and large dataset. It is capable to handle the non-linear correlation between organism and environmental factors because SOM identifies clusters and relationships between variables without the fixed assumptions of linearity or normality. The result suggested that SOM analysis was suited for understanding the relationships between bird species assemblages and habitat characteristics.
Biodiversity data management and analysis is a complex task that must be handled by biodiversity researchers. The large amount of data and complicated interaction of the data are the main problem in the biodiversity field. Data accessibility also becomes the main issue to create a data sharing environment among other biodiversity researchers. This is important element since the data is related to each other. A standardized form of data model for biodiversity data is not well implemented in real world. This study discussed about the database model for biodiversity taxonomy data (iTaxo) in order to manage the biodiversity data. We implement the Kenyir landscape which is located at the state of Terengganu in Malaysia as our case study data since the landscape is rich with biodiversity species and ecosystem. As a result, the model can be applied to manage, analyse and evaluate the biodiversity status at the landscape for conservation effort.
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