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Journal : Building of Informatics, Technology and Science

Two Factor Authentication Sistem Inventarisasi Barang dan Manajemen Dana Bantuan Operasional Sekolah Dinas Pendidikan Nasional Neneng Nuryati; Carolina Magdalena Lasambouw; Djoni Djatnika; Linda Lina Meilinda; Farida Agoes; Muhammad Rizqi Sholahuddin; Maisevli Harika
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2297

Abstract

Inventory of goods at large institutions is a complicated activity; one solution is to create a structured web application system that can be accessed anywhere. At the National Education Office, it is not only inventory management that is a problem but also the management of the School Operational Assistance Fund (BOS). Data security must be a priority because it involves significant funds and can be misused by irresponsible parties. This study aims to apply Two Factor Authentication to the Goods Inventory System and BOS Fund Management. The first stage is verification by the DISDIKNAS admin at each level of education. Next, a verification email will be sent to the registrant for verification. The results showed that the use of 2FA did not interfere with the performance of the web-based application or its users. The approval rate for the system is 97.4%. This research contributes to the implementation of website security and can be applied to similar systems
Dataset Citra Papan Sirkuit Tercetak dengan Komponen yang Terbakar Awaludin, Iwan; Gelar, Trisna; Sholahuddin, Muhammad Rizqi; Melinia, Gina; Kadhafi, Irvan; Sitepu, Rezky Wahyuda
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (593.375 KB) | DOI: 10.47065/bits.v3i3.1025

Abstract

The application of artificial intelligence, especially in the automatic optical inspection of printed circuit boards or PCBs, is increasingly being carried out by researchers. Unfortunately, the data used to train and test artificial intelligence models is synthetic data. Printed circuit boards in good condition are imaged and then changed by software to give the impression of defects. In addition, the type of damage is limited to pre-operation, namely when the PCB is not yet operational. After the PCB is operational, damage can occur, for example, burned components. Until now, there is no data set of PCB images with burned components. This study, therefore, explores data retrieval techniques that can produce the required data set. This data collection technique includes hardware setup and PCB data sources. Based on the exploration results, it is concluded that a trinocular digital microscope with high resolution can produce sharp PCB images. The obstacle that arises is the difficulty of getting PCBs with burned components. The solution was obtained by referring to the PCB repair video from the Youtube channel. Several data were collected and tested with EfficientDet with 90% mAP.