SISTEM DETEKSI OBJEK PADA KARTU TANDA PENDUDUK (KTP) UNTUK MENDUKUNG LAYANAN PASANG BARU DAN TAMBAH DAYA PT. PLN (AREA) SINGKAWANG
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Fitriana, Puji
Haris, Abdul
Cahyaningtyas, Rizqia
Haris, Abdul
Cahyaningtyas, Rizqia
Subject
Teknik Informatika
Datestamp
2022-09-23 02:32:56
Abstract :
PT. PLN (Area) Singkawang is a PT PLN Area service center that supports the electricity needs of the Singkawang community. To make it easier for officers to register applications for new plug services or add power, it is easy to fill in application data in accordance with id card on PLN's website. So a system that is able to read information on the id card quickly and accurately. By using the Google Mobile Vision platform in which the Optical Character Recognition (OCR) method algorithm has been embedded is used to convert image data into text, and then the text will be mapped into the database. Image pre-processing done by grayscale, filtering, and then perform image recognition using template matching. From the method applied, the result shown 78% accuracy and the testing accuracy of the system that was taken from 8 cm and 12 cm are 90 %.
PT. PLN (Area) Singkawang is a PT PLN Area service center that supports the electricity needs of the Singkawang community. To make it easier for officers to register applications for new plug services or add power, it is easy to fill in application data in accordance with id card on PLN's website. So a system that is able to read information on the id card quickly and accurately. By using the Google Mobile Vision platform in which the Optical Character Recognition (OCR) method algorithm has been embedded is used to convert image data into text, and then the text will be mapped into the database. Image pre-processing done by grayscale, filtering, and then perform image recognition using template matching. From the method applied, the result shown 78% accuracy and the testing accuracy of the system that was taken from 8 cm and 12 cm are 90 %.
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