JTIM : Jurnal Teknologi Informasi dan Multimedia
Vol 1 No 3 (2019): November

Deteksi Aktivitas Mencurigakan Peserta Computer Based Test Menggunakan IP Camera

Muhammad Ihsan Zul (Politeknik Caltex Riau)
Dzaky Kurniawan (Politeknik Caltex Riau)
Rahmat Suhatman (Politeknik Caltex Riau)



Article Info

Publish Date
07 Nov 2019

Abstract

Common surveillance device that used to monitor an area is known as CCTV. The CCTV will provide results in the form of video recordings, which can then be accessed by wireless communication. In its use, CCTV needs humans to monitor the real condition of the area/place. Then the use of CCTV becomes less efficient when used to oversee a place where the room rarely has movement. Because CCTV cannot detect or identify suspicious actions automatically. This research aim to develop a method that can be used to identify the activity (irregular movements) automatically. In this case, the change to be determined was the activities towards the Politeknik Caltex Riau Computer Based Test (CBT) participants. The CBT room has been employed by the IP Camera to identify participant activities. The IP camera captures the image and the image is then processed by the feature extraction method. Proposed feature exctraction method are background subtraction and pixel mapping. Pixel mapping is a method that maps objects based on specified ratio data. There are 18 ratio data generated by this feature extraction process. The determination of the illegal activities done by using the k-Nearest Neighbor. The Algorithm detects the illegal movement by using 502 datasets, and the accuracy obtained was between 98% - 98.4% with an average accuracy of 98.2% for the value of neighborliness = 3. The result can conclude that the method can identify the illegal activities of a CBT participant in the CBT room

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Journal Info

Abbrev

jtim

Publisher

Subject

Computer Science & IT

Description

Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, ...