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Media of Computer Science
Published by CV. Digital Innovation
ISSN : 30634822     EISSN : 30634997     DOI : https://doi.org/10.69616/mcs
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science
Media of Computer Science (MCS), a two times annually provides a forum for the full range of scholarly study . MCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so that more intelligent system can be built to industrial applications. The topics include but not limited to : fuzzy logic, neural network, genetic algorithm and evolutionary computation, hybrid systems, adaptation and learning systems, distributed intelligence systems, network systems, human interface, biologically inspired evolutionary system, artificial life and industrial applications. The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 2 Documents
 1 
Search results for , issue "Vol. 2 No. 2 (2025): December 2025" : 2 Documents clear
Preprocessing Image for License Plate Detection: A Systematic Literature Review Prasetyo, Riyan Bagas Dwi; Abdullayev, Vugar; Prakisya, Nurcahya Pradana Taufik; Sujana, Yudianto; Siswanto, Rahmat
Media of Computer Science Vol. 2 No. 2 (2025): December 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i2.241

Abstract

Rapid population growth contributes to an increase in the volume of vehicles, creating major challenges in their management. One potential solution is the application of deep learning-based artificial intelligence technology for automatic detection of vehicle license plates. This research uses a Systematic Literature Review (SLR) approach to evaluate the performance of various deep learning architectures in the detection process. Out of 125 articles identified, 20 articles were selected based on specific selection criteria. The analysis revealed that preprocessing techniques, such as HE, AHE, ECHE, CLAHE, and ECLACHE, have significant contributions in the processing of vehicle license plate datasets. These techniques were able to improve the visual quality of the images, thus supporting the detection process with an accuracy rate of more than 95%. This research also identified challenges, such as high computational requirements and large-scale data processing. Further research is recommended to apply preprocessing on standardized datasets to develop a reliable, efficient and sustainable detection system.
Implementation of Blockchain Technology for Securing Data Point Transactions in an IoT-Based Waste Sorting System Elriza, Naufal Raihan; Kasliono, Kasliono; Hasfani, Hirzen
Media of Computer Science Vol. 2 No. 2 (2025): December 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i2.249

Abstract

An Internet of Things (IoT) based waste sorting device awards points to users who dispose of waste through it, as long as the user is registered in the system. However, despite these benefits, this system is vulnerable to various forms of cybercrime. One such challenge is the rise of data manipulation and cyberattacks such as sql injection and threats from internal parties (Insider Threats). This research aims to secure point data transactions in an Internet of Things (IoT) based waste sorting system integrated with blockchain technology to improve security in recording user point data. Tests were conducted to ensure that point data sent from IoT devices were successfully recorded on the blockchain network permanently and verified through transaction hashes in etherscan and to prevent sql Injection and Insider Threat attacks in attempts to illegally alter data. The results of the data transmission test to the blockchain network, which was carried out 30 times, showed that each transaction was successfully recorded and provided a transaction hash. In addition, the attack test, which was carried out 30 times, each attack resulted in a notification with the text “[PERINGATAN] Terjadi Percobaan Pengubahan Poin " in red. Using the blockchain network, both attacks failed to alter user points

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