NURUL AINI SYAHMI BINTI MUHAMMAD ALI
Aini connects Computer Science with Management to make deft decisions. At the Universiti Sains Malaysia, Aini is majoring in Information System Engineering and minoring in Management. She realized the value of using Computer Science skills in business such as analytical skills, data mining, machine learning and optimization systems. Recently she finished a project which need her to build a machine learning model to predict the future outcomes. Aini is currently finishing her Bachelor of Computer Science and actively looking for a business analyst role in the near future.
Matrix No:
137147
Student Email:
Supervisor:
Ts. Dr. Chew XinYing
Supervisor Email:
SC044
Student Performance Prediction (SPP) Web Application
Despite of providing high quality of education, there are a demand on predicting student academic performance to improve the student�s quality and assisting them to achieve a great performance in their studies. One of the major issues that we faced today is the lack of existing accurate and efficient prediction model. Predictive analytics use the data, statistical algorithms, and machine learning techniques to identify the feasibility of future outcomes based on historical data which can help institution to do a better decision making. Machine learning is an area of application where artificial intelligence is applied, empowering the system to learn and act from experience without the requirement of an explicit program. Future events can be predicted by executing machine learning algorithms on the previous data. For this project, we will train and test the data sets by using some of Machine Learning algorithms. Algorithm with the best performance will be chosen to be implement in our model. Besides, the user can enter a new value for the features to make the prediction. The results of the prediction will show the student�s performance in the future whether it is good, average, or poor. Lastly, the data will be visualized by using a dashboard to make it more comprehensible to the users.