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All Journal JTERA (Jurnal Teknologi Rekayasa) REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Industrial Research Workshop and National Seminar Media Elektrik
Muhammad Yusuf Fadhlan
Politeknik Neger Bandung
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Other

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Journal : Media Elektrik

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SYSTEM DESIGN FOR CALCUALTING THE NUMBER AND DENSITY OF MOTORCYCLES IN PARKING AREA BASED ON BACKGROUND SUBTRACTION METHOD Muhammad Yusuf Fadhlan; Auliya Rahmawati; Novita Lestari Anggreini
Jurnal Media Elektrik Vol. 21 No. 2 (2024): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v21i2.1536

Abstract

There are still issues with a number of students parking their vehicles improperly in the parking spaces provided. This causes suboptimal parking capacity due to a lack of information about parking capacity. In recent years, at a certain library, vehicle detection has been implemented using a Gaussian mixture model algorithm using a Raspberry Pi. However, this library does not provide information about the density status of the parking area. Therefore, an information system was created to determine the level of density of the parking area based on the ratio of vehicles entering and exiting compared to the maximum capacity of the parking area. The system uses the Gaussian mixture model algorithm with the machine learning method of background subtraction MOG2, which can calculate the number of vehicles based on the difference between objects and the background of objects, using test data in the form of videos recorded using a camera positioned horizontally to the entrance and exit lanes of the parking area. This research resulted in an accuracy of 89.7% for Video1TA, precision of 93.2%, a crowded parking area density level, and a value of 129.12. Video2TA had a value of 101.08, precision of 100%, and accuracy of 90%, while Video3TA had an accuracy of 35%, precision of 56.7%, and a value of 49.48. The density levels of videos 2 and 3 are the same, indicating that the parking area is still empty. The test results show that the value can affect the system in detecting an object.
Co-Authors Adyatma Adyatma Auliya Rahmawati Feni Isdaryani Firman Akbar Maulana Haidar, Andry Hudaya, Rida Luthfiana Adam Maldini Maya Rahayu Mohamad Rifki Aulia Muhammad Hilman Maulana Nadya Sarah Novita Lestari Anggreini Nugroho, Hertog Regina Nur Shabrina Supriyadi, Tata Supriyanto Suhono W. Tri Hartono ‪Usman Balugu Hanafi