SISTEM KEAMANAN PANEL SEL SURYA BERBASIS PEMINDAI WAJAH MENGGUNAKAN ALGORITMA DEEP LEARNING

PUTRA, MUHAMMAD IQBAL AGUNG TRI and Hikmarika, Hera and Dwijayanti, Suci and Suprapto, Bhakti Yudho (2020) SISTEM KEAMANAN PANEL SEL SURYA BERBASIS PEMINDAI WAJAH MENGGUNAKAN ALGORITMA DEEP LEARNING. Undergraduate thesis, Sriwijaya University.

	Text RAMA_20201_03041281520109.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (11MB) | Request a copy
	Text RAMA_20201_03041281520109_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (14MB) | Request a copy
Preview	Text RAMA_20201_03041281520109_0007127801_0030078404_0011027503_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (999kB) | Preview
	Text RAMA_20201_03041281520109_0007127801_0030078404_0011027503_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (740kB) | Request a copy
	Text RAMA_20201_03041281520109_0007127801_0030078404_0011027503_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (57kB) | Request a copy
	Text RAMA_20201_03041281520109_0007127801_0030078404_0011027503_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (3MB) | Request a copy
	Text RAMA_20201_03041281520109_0007127801_0030078404_0011027503_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (229kB) | Request a copy
	Text RAMA_20201_03041281520109_0007127801_0030078404_0011027503_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (149kB) | Request a copy
	Text RAMA_20201_03041281520109_0007127801_0030078404_0011027503_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) | Request a copy

Abstract

Utilization of energy sourced from solar power as alternative energy requires solar panels. However, the high panel price makes the panel vulnerable to theft, so a security system that can monitor the panels throughout the day is needed. One way that can be done to maintain the security of the panel is to use a face recognition-based security system. Some security system studies using surveillance cameras (CCTV or webcam) that have face scanning systems have been carried out. However, the security system has shortcomings such as not being able to recognize unknown faces, the system has not worked in realtime (online), and does not have a centralized storage system. Therefore, this research develops a face scanner-based solar cell panel security system using deep learning algorithm in real time and integrated with a database system. The system will recognize two faces that are believed to be people known using a model that has been created with the FaceNet method and the Deep Belief Network (DBN) algorithm. Every face that is detected will have a probability of being similar to a face that is in the database. If the probability is below a certain value, it is believed that the face is an unknown face and the system will automatically capture the face image and send it to the database system. The results of testing this security system indicate that the value of the success of facial recognition of moving images that are not recognized in offline testing is 94.4% and in online testing is 87.5%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Pengenalan Wajah, Sistem Keamanan, FaceNet, Deep Belief Network (DBN), Real Time, Database
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics > TK7816.P39 Electronics T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK8300-8360 Photoelectronic devices (General)
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Users 4677 not found.
Date Deposited:	23 Apr 2020 02:03
Last Modified:	23 Apr 2020 02:03
URI:	http://repository.unsri.ac.id/id/eprint/28900

Actions (login required)

View Item