Clustering on CS230’s alumni data for employment using K-Means / Siti Norainul Faraha Muhammad Anuar
Computer Science (CS) is a subject or a course for some universities. In Universiti Teknologi Mara (UiTM), CS or is known as CS230. There is a problem where it is not confirmed if the CS230's alumni work in that field or not. Hence, a research that includes gathering information of big number...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2015
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ir.uitm.edu.my/id/eprint/14595/1/TD_SITI%20NORAINUL%20FARAHA%20MUHAMMAD%20ANUAR%20CS%2015_5.pdf |
| الوسوم: |
إضافة وسم
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| الملخص: | Computer Science (CS) is a subject or a course for some universities. In Universiti Teknologi Mara (UiTM), CS or is known as CS230. There is a problem where it is not confirmed if the CS230's alumni work in
that field or not. Hence, a research that includes gathering information of big number of important data of alumni may be done to solve the problem. The proposed system will include data gathering, data extraction, data analysis by using K-Means technique and data visualization. The extraction will be done on the data of alumni that is obtained from Office of Industry Community and Alumni Network (ICAN). The data involved is Cumulative Grade Point Average (CGPA) and employment. Then, the result will be presented as visualization or graphic. This may shows the important results clearly. |
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