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All Journal Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Telematika Zonasi: Jurnal Sistem Informasi SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Algoritma, Logika dan Komputasi JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Evasaria Magdalena Sipayung
Program Studi Informatika, Fakultas Teknologi Dan Desain, Universitas Bunda Mulia
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Journal : Jurnal Algoritma, Logika dan Komputasi

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Decision Support System in Used Motorcycle Selection Using Simple Additive Weighting (SAW) Method Evasaria Magdalena Sipayung
Jurnal Algoritma, Logika dan Komputasi Vol 5, No 1 (2022): Jurnal ALU, Maret 2022
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v5i1.3628

Abstract

PD X is a used motorcycle (mokas) retail company located in Subang, West Java. PD X sold their mokas to general public in Subang. PD X buys mokas from individual who comes to PD X dealership and from the auction which uses motorcycle. Problem faced PD X right now was wrong of choosing right mokas precisely that accumulated stock of mokas. Incorrectly predicted mokas criteria in accordance with customer needs that lead to long mokas sales-cycle time each month. There are 6 mokas criteria to consider when choosing mokas in the auction including brand/type, price limit, color, production year, vehicle registration renewal (STNK), and the vehicle registration existence. The purpose of this research make DSS (Decision Support System) using SAW (Simple Additive Weighting) method so can help PD X to choose the best mokas and select brands based on auction document according to customer needs and replenish the mokas stock that has run out. Implementation of the programming language used Java with SQL Database System. The DSS system displays the best mokas by choosing mokas which has the highest ranking.
VEHICLE LICENSE PLATE DETECTION USING YOLO ALGORITHM Kenneth Christoper Nugraha; Evasaria Magdalena Sipayung
Jurnal Algoritma, Logika dan Komputasi Vol 6, No 2 (2023)
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v6i2.4739

Abstract

Urban population growth has created challenges in efficient parking space management. Manual data collection is time-consuming and error-prone, especially at night. Modern technology-based solutions are urgently needed. This research focuses on an innovative parking management system using YOLO for real-time object detection, including license plates. The objective is to assess the YOLO algorithm's accuracy in license plate detection. The methodology follows software development best practices, utilizing Python and Tkinter GUI for an intuitive interface. YOLO and EasyOCR enable object detection and character recognition. Results show high accuracy: 88.8% for HD and 86.3% for sub-HD resolutions. YOLO proves reliable for license plate data collection, reducing manual intervention and enhancing parking management.
Co-Authors Aditia Wigantara Adigoena Calvin Christopher Citra Cut Fiarni Cut Fiarni Fiarni Halim Agung Kenneth Christoper Nugraha Rarasati, Dionisia Bhisetya Sherly Sutopo Tamsir Hasudungan Sirait Teady Matius Surya Mulyana, Teady Matius Thomas Lucky Prasojo Willy Stevanus Susilo