PREDICTING THE EFFECTIVENESS OF WEB INFORMATION SYSTEMS USING NEURAL NETWORKS MODELING: FRAMEWORK & EMPIRICAL TESTING
Journal Title: International Journal of Software Engineering and Computer Systems - Year 2018, Vol 4, Issue 1
Abstract
The information systems (IS) assessment studies have still used the commonly traditional tools such as questionnaires in evaluating the dependent variables and specially effectiveness of systems. Artificial neural networks have been recently accepted as an effective alternative tool for modeling the complicated systems and widely used for forecasting. A very few is known about the employment of Artificial Neural Network (ANN) in the prediction IS effectiveness. For this reason, this study is considered as one of the fewest studies to investigate the efficiency and capability of using ANN for forecasting the user perceptions towards IS effectiveness where MATLAB is utilized for building and training the neural network model. A dataset of 175 subjects collected from international organization are utilized for ANN learning where each subject consists of 6 features (5 quality factors as inputs and one Boolean output). A percentage of 75% o subjects are used in the training phase. The results indicate an evidence on the ANN models has a reasonable accuracy in forecasting the IS effectiveness. For prediction, ANN with PURELIN (ANNP) and ANN with TANSIG (ANNTS) transfer functions are used. It is found that both two models have a reasonable prediction, however, the accuracy of ANNTS model is better than ANNP model (88.6% and 70.4% respectively). As the study proposes a new model for predicting IS dependent variables, it could save the considerably high cost that might be spent in sample data collection in the quantitative studies in the fields science, management, education, arts and others.
Authors and Affiliations
Kamal Moh’d Alhendawi
Keywords
Related Articles
- EP ID EP597368
- DOI -
- Views 105
- Downloads 0
MODELING AND SIMULATION OF TRAFFIC FLOW: A CASE STUDY - FIRST RING ROAD IN DOWNTOWN MADINAH
Traffic assessment is extremely important for the performance evaluation of vehicle-flow on a road network. This paper presents an assessment of traffic flow on the busiest road i.e., First Ring Road located at the centr...
A NEW FRAMEWORK FOR PREDICTING THE IMPACT OF TRAFFIC ON THE PERFORMANCE OF MOBILE AD-HOC NETWORK (MANET): USING REGRESSION AS DATA MINING APPROACH
With the rapid technological advances in wireless communication and the increasing of usage of portable computing devices, it is expected that mobile ad hoc networks are increasingly developed towards enhancing the flexi...
PERFORMANCE EVALUATION OF SELECTED DISTANCE-BASED AND DISTRIBUTION-BASED CLUSTERING ALGORITHMS
Clustering is an automated search for hidden patterns in a datasets to unveil group of related observations. The technique is one of the viable means by which the patterns or internal structure of the data within the sam...
THE NEED OF DASHBOARD IN SOCIAL RESEARCH NETWORK SITES FOR RESEARCHERS
Nowadays, dashboard has been widely used by organizations to display information based on their objectives such as monitoring business performance or checking the current trend in the niche market. There is a need to inv...
PARAMETER-LESS SIMULATED KALMAN FILTER
Simulated Kalman Filter (SKF) algorithm is a new population-based metaheuristic optimization algorithm. In the original SKF algorithm, three parameter values are assigned during initialization, the initial error covarian...