| 000 | 02845nam a2200265 a 4500 | ||
|---|---|---|---|
| 001 | vtls000076638 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204603.0 | ||
| 008 | 140121t2013 my a f m 001 0 eng d | ||
| 020 | _aTHE0003671(Local) | ||
| 039 | 9 |
_a201905161355 _bzulaiha _c201408290940 _dFida _y201401211503 _zFida |
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| 040 | _aUMP | ||
| 090 | _aTK5105.65 .Y46 2013 rs Bc. | ||
| 100 | 0 | _aYeow, Jian Qin | |
| 245 | 1 | 0 |
_aStudent location prediction in campus / _cYeow Jian Qin |
| 260 |
_aKuantan, Pahang : _bUMP, _c2013 |
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| 300 |
_ax, 58 p. : _bill. (some col.) ; _c30 cm. |
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| 502 | _aProject paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2013 | ||
| 504 | _aBibliography: p. 49-51 | ||
| 520 | 3 | _aStudent Location Prediction in Campus system is an application that uses the Naïve Bayes algorithm to predict the most probable locations of the selected student in the future. The aim of this thesis is to prove that location prediction for students in campus can be implemented using Naïve Bayes algorithm. This research is proposed to ease user when perform various tasks that need the location prediction for example lecturers and colleagues. It also can minimize the continuous usage of internet connection or GPS connection when using the application. Naïve Bayes algorithm is a type of classifiers that uses a probabilistic approach with naïve independence or conditional independence. Naïve Bayes algorithm is used in this study due to its simple structure and fast construction speed. It is one of the most popular data mining algorithms used by Google Inc. in Gmail. It has high accuracy and precision and has been used in various industries like spam filtering. The system will be developed using the Agile Model Driven Development software model that uses iterative approach in the software development life cycle. It is developed using Microsoft Visual Studio 2010 and C# programming language. The implementation of Naïve Bayes algorithm to predict the location of the student can be done through the application. The location prediction results obtained and the real time data are matched. It shows that the accuracy and precision of Naïve Bayes algorithm in human location prediction because the location predicted same with the real time data. All of the objectives are met in this project. This thesis concluded that implementation of Naïve Bayes algorithm into the student location prediction is successful and more research on human location prediction can be done in the future to enhance the human location prediction in location based service. | |
| 650 | 0 | _aLocation-based services | |
| 650 | 0 | _aGeographic information systems | |
| 650 | 0 | _aLocation-based services | |
| 999 |
_aVIRTUA40 _c4623 _d4629 |
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