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The increasing intensity of traffic object movement in urban areas has not been accompanied by adequate road infrastructure, resulting in traffic congestion, air pollution, and a higher risk of traffic accidents. One of the primary causes of accidents is traffic violations, particularly wrong-way driving behavior. This study develops a video-based automated traffic violation detection system using the YOLOv5 algorithm. A computer vision approach is employed to detect, classify traffic objects, and count wrong-way violations in real time. Due to limited access to real-world traffic violation footage, simulated traffic scenarios are used as testing data. The system is evaluated on four traffic object classes: motorcycles, cars, buses, and trucks. Experimental results demonstrate strong performance, achieving a precision of 90%, a recall of 92%, and an F1-score of 91%, while the traffic object counting accuracy reaches 89%. These findings indicate that the proposed system has significant potential to support traffic analysis and assist authorities in making more effective decisions to reduce congestion and traffic accidents.

Traffic violations are one of the serious problems frequently occurring in various regions, including Binjai City. Various types of violations, such as disobeying road signs and markings, incomplete vehicle documents, and violations that threaten the safety of drivers and other road users, continue to increase despite preventive and repressive efforts carried out by the authorities. This condition indicates that handling traffic violations cannot rely solely on field enforcement but also requires the support of technology capable of analyzing data more comprehensively. This study aims to predict the level of traffic violations by applying the Naïve Bayes method through data mining techniques. The dataset used consists of traffic violation records in 2023 from the Binjai City Police Department, with the main variables including violations of traffic signs and markings, document completeness, and safety-related violations. The Naïve Bayes method was selected because of its ability to perform classification with good accuracy, simplicity, and efficiency in processing large amounts of data. The implementation of this research is realized by developing a web-based application using Visual Studio Code as the development environment and MySQL as the database system. The results of this study are expected to provide structured information regarding traffic violation patterns, support authorities in making more effective decisions, and serve as an alternative solution in the prevention and handling of traffic violations in Binjai City.

PT. PLN (Persero) UP3 Binjai faces challenges in handling electricity usage violations that increase every year. Lack of utilization of data violations that can be utilized to produce useful information in supporting strategic decision making by PLN, especially in the implementation of Electricity Usage Control (P2TL) activities. This study aims to identify customer violation patterns based on rayon, power, and type of violation with data mining methods using the K-Means Clustering algorithm. The results of the study show that the 3rd cluster represents the most violation-prone area, namely in the West Binjai Rayon, with a power of 450 VA and the most frequent type of P2 violation. The results of the study show that the K-Means algorithm with the Elbow method is able to systematically group data violations based on certain characteristics. The results of this study can provide recommendations to PLN UP3 Binjai to improve the effectiveness of monitoring and enforcement strategies through a more targeted approach.  

Infrastructure development in urban areas is often faced with various challenges, including ethical issues. The jetty construction project at Pantai Mutiara in Block SB Number 15 A, North Jakarta, is one prominent example in this regard. The jetty, designed to support maritime and tourism activities, has, since its inception, presented a range of issues related to ethical violations. These include manipulation of permits, misuse of funds, disregard for environmental impacts, and exploitation of labour. The ethical violations in this project not only harmed the environment and surrounding communities, but also undermined public trust in the government and related agencies. This case shows how important integrity, transparency and responsibility are in every stage of development. Through this study, we will take an in-depth look at the various aspects of the ethical violations that occurred in the jetty construction project at Pantai Mutiara, including the causes, impacts, and efforts that can be made to prevent similar occurrences in the future. By identifying and understanding the ethical breaches that occurred, it is hoped that valuable lessons can be learnt that can be applied to other development projects in Indonesia. Ultimately, the aim of this paper is to provide constructive recommendations to improve the planning and implementation process of infrastructure projects, so as to achieve a balance between development progress and the ethical principles that must be upheld.