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Adri Priadana
Teknik Informatika, Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta
Computer Science & IT

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Performance Analysis of Illumination Invariant Change Detection Method for Detecting Image Change in Night Vision Camera Adri Priadana
Compiler Vol 8, No 2 (2019): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1054.897 KB) | DOI: 10.28989/compiler.v8i2.514

Abstract

At present, the use of video cameras is not only limited to documenting events but is also used for surveillance systems. Changes in lighting that occur in the surveillance area is one of the problems that result in a false alarm on the surveillance system. Illumination Invariant Change Detection is a method for detecting image changes on images. This study aims to determine the performance of the Illumination Invariant Change Detection method to detect image changes in night vision surveillance cameras. The Illumination Invariant Change Detection method does not work well for detecting image changes on a night vision camera under dark lighting conditions at an average value of Lux 0 with an infrared lamp on. The accuracy of the application of the method to detect image changes on night vision cameras is 80% with the selection of the threshold value of the detection of image changes that is 75000 pixels.
Implementation and Performance Analysis of Private Cloud Using Openstack Swift and Rclone Candra Aditama; Adri Priadana
Compiler Vol 8, No 1 (2019): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1332.694 KB) | DOI: 10.28989/compiler.v8i1.428

Abstract

Many companies need a storage system that can be accessed in real time by all parts of the company. Most digital data storage methods today still use conventional methods where data is stored on an external hard disk or public cloud. Storage with external hard disk media makes accessing data difficult and has the risk of data loss when storage media is damaged. On the other hand, the storage method using public cloud requires an internet connection with large bandwidth requirements and the company still has to spend a budget on renting it. This study aims to design digital data storage methods using a private cloud that can be accessed in real time by all parts of the company without having to spend a budget on hiring a storage media and renting an internet connection with large bandwidth requirements. A private cloud was built using OpenStack Swift as an object storage service provider and Rclone as a cross-platform computer data management application. The results of this study are the creation of a private cloud that runs object storage services using Swift storage objects with relatively light and high scalability to meet the needs of storing data effectively and efficiently. A private cloud-based data storage media with relatively light and high scalability to meet data storage needs. Data storage media that can be accessed easily without having to use an internet connection with large bandwidth requirements.
Co-Authors Candra Aditama