FINGERPRINT REGISTRATION FRAUD DETECTION USING TIGHT CLUSTERING ON EMPLOYEEâS PRESENCE AND ACTIVITY DATA
Detecting fraud in fingerprint registration poses a unique challenge as we cannot rely on an existing employee’s attribute. Furthermore, analyzing using a supervised algorithm cannot handle unlabeled data that generated uniquely for this case. We study the patterns of employee’s presence and acti...
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Main Author: | Kamil, Irfan |
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Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/70698 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
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