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Jakarta, the capital of Indonesia, is known for its high congestion levels. Data from the TomTom Traffic Index shows that Jakarta ranked 30th in the world in 2023 as one of the most congested cities, with a congestion level reaching 53% during peak hours. Pisangan Lama in East Jakarta is one of the densely populated areas, adjacent to busy roads. The main campus of STIKOM CKI, also located in East Jakarta, is situated along a route prone to heavy traffic. Given the congestion issues and the lack of information on the nearest routes, this study aims to implement the A* algorithm to find the shortest route from Pisangan Lama, East Jakarta, to the main campus of STIKOM CKI. The A* algorithm is chosen for its optimal routing capabilities. Based on research on three routes (Jl. I Gusti Ngurah Rai, Jl. Basuki Rachmat, and Jl. Raya Kalimalang), the results show that the route via Jl. Basuki Rachmat is the shortest, with a distance of 7.7 km. The implementation of the A* algorithm is expected to provide an efficient solution for the community in finding the nearest route.

This paper aims to find out the process of issuing permits for checking and unloading cargo outside the customs area at the customs and excise office, this application must have a permit that must be fulfilled to be managed by the agent, because the implementation of checking and unloading cargo outside the designated area without obtaining a permit can be subject to criminal sanctions as regulated in Article 102 letter (b) of Law Number 17 of 2006 concerning Customs Due to port congestion, ships can dock outside the customs area (out custom area) by fulfilling certain requirements and following the procedures set by the Customs and Excise authorities. in managing permits, agents often encounter obstacles or constraints when issuing permits that are detrimental to certain parties. Therefore, the responsible party of PT. Bahari Eka Nusantara Belawan branch must coordinate and have accurate accuracy in the process of issuing this permit. The role of PT. Bahari Eka Nusantara Belawan branch is very important for parties who participate in the process of managing permits outside this area. This permit is crucial to avoid criminal charges against those responsible for checking and unloading outside the customs area. It can be concluded that there are still obstacles or errors in data input that can cause delays in approval of permits for checking and unloading outside the customs area.

In Surabaya City, the City Government through the Transportation Agency developed the Suroboyo Bus and Trans Semanggi programs to address traffic congestion, limited public transportation, and the need for safe, comfortable, and environmentally friendly transportation. However, complaints are still found regarding limited facilities, irregular schedules, and suboptimal communication services, so that service performance evaluation is needed from the user's perspective. This study aims to analyze the performance of Suroboyo Bus and Trans Semanggi public transportation services at the Surabaya City Transportation Agency using five public service performance indicators according to Dwiyanto et al. (2021), namely productivity, service quality, responsiveness, responsibility, and accountability. The approach used is quantitative with the Importance Performance Analysis (IPA) method. The results of the study show an average expectation score (importance) of 4.18 and a reality score (performance) of 3.86 with an overall gap of -0.32, which means that the performance of Suroboyo Bus and Trans Semanggi services still does not meet public expectations. Through the IPA mapping, three attributes are in Quadrant I (high priority): the friendly and professional attitude of staff, the adequacy of on-board facilities, and the transparency of official information regarding schedules and service changes. A total of 13 attributes are in Quadrant II (maintained), 13 attributes in Quadrant III (low priority), and one attribute in Quadrant IV (excessive).

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.

This study aims to analyze the differences in motorcycle traffic flow (Q) during the morning and afternoon peak hours as an indicator of roadway operational performance, referring to the Indonesian Road Capacity Guidelines (PKJI) 2014, with a case study on Mawar Street–Wijaya Kusuma Street, Jember Regency. The research data were obtained from 12 observation points through traffic surveys that recorded motorcycle traffic flow in vehicles per hour (veh/h). The analytical methods used include descriptive statistical analysis, normality testing, and paired sample t-test. The results show that the average motorcycle traffic flow during the morning peak hour is 115.58 veh/h with a standard deviation of 62.97, while during the afternoon peak hour it is 63.25 veh/h with a standard deviation of 28.57. The paired sample t-test yields a significance value of 0.015 (p < 0.05), indicating a statistically significant difference between morning and afternoon traffic flows. These findings suggest that the level of roadway capacity utilization is higher during the morning peak hour, which is closely associated with dominant routine travel activities such as commuting to work and school. The results of this study are expected to serve as a basis for evaluating roadway operational performance and to support traffic management and traffic engineering planning aimed at improving road network performance and reducing congestion.

This study focuses on the analysis of traffic density in Jember City, particularly at the Wirolegi Intersection, which is known to have a high density level. This condition often triggers congestion that hinders public mobility, so that appropriate and data-based handling efforts are needed. The purpose of this study is to identify and analyze the level of density at critical congestion points through a statistical approach using the One Way ANOVA method. The research method used is quantitative descriptive with a descriptive observational approach. Primary data was collected directly through a field survey in 2025 at the Wirolegi Intersection as one of 3 intersections in Jember City. The data obtained were then processed using normality tests, homogeneity tests, and One Way ANOVA with the help of SPSS software. The results of the analysis show that the traffic flow density on the three routes studied, namely Jalan Gunung Haryono, Jalan Brigjen Katamso, Jalan Yos Sudarso, does not show a significant difference. The significance value of the ANOVA test is greater than 0.05 which indicates the similarity of density levels between routes. Further testing (post hoc testing) also strengthens this finding. The conclusion of this study shows that handling congestion at the Wirolegi Intersection needs to be done comprehensively through traffic control and evaluation of the transportation system to improve smoothness and mobility in Jember City.

This research examines the influence of road infrastructure development on local economic growth in Medan City, emphasizing its role in improving accessibility and supporting economic activities. Road infrastructure is a vital component of regional development, as it facilitates the movement of goods and services, reduces transportation costs, and enhances connectivity between economic centers. Well-developed road networks can stimulate business expansion and encourage investment by creating a more efficient economic environment. The study employed a descriptive quantitative approach using field surveys involving 20 respondents, including business actors, local residents, and government representatives. Data were collected through structured questionnaires and analyzed descriptively to capture perceptions regarding the economic impact of road infrastructure development. The results indicate that improvements in road quality, capacity, and connectivity have a positive influence on local economic growth. Respondents reported increased trade activities, improved access to markets, higher investment opportunities, and rising community income levels as direct benefits of improved road infrastructure. However, the study also identified several challenges that may hinder long-term economic outcomes. Traffic congestion, uneven infrastructure development across areas, and inadequate routine maintenance were highlighted as significant issues. These problems can reduce efficiency and limit the sustainability of economic gains. Therefore, continuous government commitment, effective maintenance strategies, and equitable distribution of infrastructure development are essential. Strengthening coordination among stakeholders is also necessary to ensure that road infrastructure development supports inclusive and sustainable local economic growth in Medan City.

Traffic congestion is a persistent challenge in urban areas in Indonesia, where increasing vehicle density creates the need for intelligent traffic monitoring systems. This study aims to develop a real-time vehicle parking system using the YOLOv8 object detection model to provide efficient traffic analysis from live CCTV broadcasts and recorded videos. This study uses a quantitative experimental approach with the implementation of the YOLOv8m model using the Ultralytics library in Python, tested on data collected from CCTV cameras A TCS Dishub Medan and additional footage from mobile devices. Vehicles are detected and counted in two directions up (Up) and down (Down) using virtual detection lines on the video frame. The system performance is evaluated by automatic detection counting with manually recorded ground truth data. The results show that on live CCTV broadcasts, the YOLOv8m model achieves an average precision of 98.96%, a recall of 96.59%, and an F1 score of 97.74% for upstream traffic, while for downstream traffic it achieves 100% precision, 95.64% recall, and an F1 score of 97.730/0. On the other hand, on high-quality recorded videos, all performance metrics achieve 100%, indicating perfect detection accuracy. These findings confirm the effectiveness of YOLOv8 in real-time traffic monitoring, but also indicate that video quality and stream stability affect detection performance. In conclusion, the developed system shows strong potential to support smart city traffic management solutions. Future research should focus on performance optimization under low-resolution live streaming conditions to improve accuracy in practical applications.  

The study aims to improve the passion fruit syrup production system at Harisma Home Industry, which has been hindered by an inefficient facility layout and complicated raw material flow. These issues lead to longer processing time, higher operator workload, and reduced production capacity. To solve this, the research uses the Activity Relationship Chart (ARC) and Total Closeness Rating (TCR) to evaluate and redesign the layout. TCR results show that the Raw Material Warehouse has the highest priority with a score of 119, requiring an Absolutely Important (A) relationship with the Production Room. The Parking Area and Waiting Room also fall into the Absolutely Important category, as they support smooth movements of materials and visitors. Meanwhile, the Toilet has a Very Important (E) relationship with the Waiting Room due to comfort and accessibility needs. Based on these proximity requirements, a new layout was designed by placing the Raw Material Warehouse next to the Production Room to create a faster and more efficient material flow. Other facilities were rearranged to minimize unnecessary movement. This new layout is expected to streamline processes, reduce congestion, and enhance overall capacity and operational performance.

Salam Pacific Indonesia Lines is a company included in the largest domestic shipping industry in the field of logistics and sea transportation services with a focus on inter-island container transportation in Indonesia using ships. This paper aims to determine how the container utilization strategy in improving logistics efficiency by PT. Salam Pacific Indonesia Lines Medan Branch. The process begins with selecting the right type of container, standardization and consolidation of cargo, integration of digital logistics systems, and optimization of routes and modes of transportation. In compiling this paper, the author applies several methods, including field studies or direct observations in the field, and library studies or literature reviews. The goal is to understand more deeply how PT. Salam Pacific Indonesia Lines Medan branch implements a container utilization strategy to improve efficiency in logistics activities. The obstacles faced in handling this are fleet and vehicle constraints, limited promotion and adjustment of application technology, traffic congestion, and weather and safety factors. In addition, inefficiencies in the distribution process, lack of good cooperation and coordination, and technological limitations are obstacles in optimizing container use. Good coordination can improve the service of goods delivery activities so that they can run smoothly, safely and efficiently.

This study was conducted with the aim of analyzing the difference invehicle traffic volume in the morning and afternoon on the Moch.Sruji-Jalan PB.Sudirman road section in Jember Regency. The survey was conducted through field observationby directly recording vehicle volume at 15-minute intervalsminutes, covering four categories of vehicles: heavy vehicles, light vehicles, motorcycles, and non-motorized vehicles. The data obtained was analyzedusing a quantitative approach assisted by the SPSS application, including a normality testand a mean difference test to determine the significance of the difference invehicle volume between the two observation times. Descriptively, traffic flowin the morning had a higher volume, especially during peak hoursaround 06.00-08.00 with a total of 450-500 vehicles, whilein the afternoon it was in the range of 250-350 vehicles. In addition, motorcycleswere the most dominant type of vehicle in traffic flow compared toother vehicle categories. The conclusion of this study is that the pattern ofcommunity activity, which is more intense in the morning, makes this perioda peak hour with the potential to cause congestion. The results of this studyare expected to be taken into consideration in the formulation of targeted traffic engineering policiesin the study area.

Overburden removal is a critical phase in coal mining operations, as it directly affects production continuity and operational efficiency. However, production realization often deviates from the mine plan due to various operational constraints. This study, conducted at Pit K1 Mahakam of PT. Insani Baraperkasa, evaluates the causes of underachievement in overburden stripping targets using the Six Big Losses framework, which classifies inefficiencies into Breakdown Losses, Setup and Adjustment Losses, Idling and Minor Stops, Reduced Speed Losses, Process Defect Losses, and Reduced Yield Losses. The analysis revealed that the dominant losses were Reduced Speed Losses (26%) and Setup and Adjustment Losses (10%), primarily caused by disposal congestion, shift changes, and repairs at the loading and disposal areas. Minor contributions were found from idling (3%), production losses (5%), while breakdown losses showed negligible impact. These factors led to increased standby time and reduced equipment cycle effectiveness. Improvement strategies are recommended through optimized disposal allocation, reduction of waiting time, and stricter control of external operational disruptions to enhance stripping efficiency and achieve production targets.

Unmonitored traffic conditions often hinder decision-making processes in traffic management, particularly on secondary roads. Jalan Raden Inten II in East Jakarta is one of the connecting routes with heavy traffic activity at certain times, yet no integrated data-based monitoring system is currently available. This study proposes an Internet of Things (IoT)-based traffic condition classification system to identify Clear, Normal, or Congested states based on vehicle counts and speed categorization. The system is designed using an ESP32 microcontroller, an HB100 sensor to detect vehicle speed, and two AJ-SR04M ultrasonic sensors to detect vehicle presence. Data on vehicle counts and the percentage of slow-moving vehicles are periodically transmitted to the ThingSpeak platform and processed using the Threshold-Based Classification method. The classification results are visualized on a dashboard-based website equipped with charts, traffic condition status, and notifications when consecutive congestion is detected. Testing was conducted using simulation data over a specific period. Qualitative validation was carried out by comparing the classification results with traffic indicators from Google Maps. The results show that the system can classify traffic conditions with a good degree of agreement with external references, although discrepancies occurred at certain times due to the limitations of simulated data. This research demonstrates that a simple IoT approach can provide an affordable and effective solution for monitoring and classifying traffic conditions, with potential for real-world implementation in future studies.

Lengthy, disorganized physical queues in conventional food ordering systems, particularly within canteens, significantly compromise customer convenience and operational efficiency. This direct-ordering model often results in crowd congestion, unpredictably long waiting times, and potential friction among patrons. To address these operational issues and substantially enhance user satisfaction, this research proposes the development and implementation of an innovative Web-Based Food Ordering System. This digital platform allows customers to place orders entirely online, effectively eliminating the need for physical queuing. The system's core functionality is the realtime monitoring of order status and queue position, providing transparent information directly to the customer's device. For canteen management, the application offers a crucial tool for integrated and structured order handling, ensuring staff can prepare meals more accurately and promptly. By transforming the ordering process into a streamlined digital workflow, the system is expected to accelerate the service cycle, minimize unnecessary crowding, and substantially improve customer satisfaction through a modernized, well-organized, and highly efficient experience. This initiative represents a significant step toward smarter and more responsive food service operations.

Container loading and unloading procedures are a series of essential operational activities carried out to systematically, safely, and efficiently move containers from ships to the stacking yard or vice versa. This study aims to examine these procedures, analyze the effectiveness of their implementation, and identify the obstacles and corrective efforts encountered in the field. The methods used include field observation (field research) and literature review (library research). The results indicate that the procedural stages involve document preparation (Bill of Lading and Manifest), ship berthing, the utilization of various loading and unloading equipment (such as Gantry Crane, RTG, and Headtruck), and container arrangement within the Container Yard (CY). The process involves three main work stages: Stevedoring, Cargodoring, and Receiving/Delivery, which require close coordination among port operators, foremen, and Stevedoring Workers (TKBM). Implementation can be hindered by crane breakdowns, headtruck limitations, traffic congestion, and slow stevedoring performance. Effective solutions suggested include routine equipment maintenance, increasing HT fleet capacity, enhancing human resource competency through training, and coordinating traffic routes with relevant authorities. Optimal procedure execution is crucial for ensuring smooth logistics flow, time efficiency, and occupational safety.

This study provides an in-depth analysis of the benefits of implementing a SAP-based Enterprise Resource Planning (ERP) system for end-users at PT XY, an Indonesian airport management company. A qualitative case study approach was applied through comprehensive in-depth interviews and direct observations of accounting division staff who actively utilize the SAP Financial Accounting (FI), Controlling (CO), and Materials Management (MM) modules as part of their daily operations. The findings demonstrate that SAP implementation significantly enhances work efficiency, data accuracy, and overall operational productivity across multiple business processes. The system facilitates seamless cross-departmental integration, reduces manual errors, accelerates financial reporting, and supports real-time, data-driven decision-making. Furthermore, SAP strengthens internal coordination by providing consistent, centralized, and easily accessible information to all relevant stakeholders. Key challenges identified include limited network access, server congestion during peak hours, and difficulties with remote connections when accessing the system outside the office environment. The company addressed these issues through regular user training, provision of secure Virtual Private Network (VPN) access, expansion of server capacity, and a strategic plan to migrate to cloud-based SAP S/4HANA to improve flexibility, scalability, and long-term system reliability. The findings not only enrich the literature on ERP adoption, with practical guidance for other organizations seeking to plan, implement, and evaluate ERP systems to meet their own business needs, including effective human resource planning and change management strategies.

Efficient management of patient queues is essential in healthcare systems to ensure timely care, optimize resource utilization, and enhance patient satisfaction. Mathematical programming, particularly when applied in conjunction with queuing theory and optimization models, provides a rigorous framework for analyzing and improving healthcare service delivery. This approach involves modeling arrivals and service processes, applying queuing models (such as single-server, multi-server, and priority queues), and formulating optimization objectives—often to minimize total costs, patient waiting times, or resource idling. Recent research demonstrates that combining queuing theory with mixed-integer programming and simulation techniques enables healthcare managers to allocate resources dynamically, set staffing levels, and assign priorities among different patient categories. For example, the use of mixed-integer programming can determine the optimal number of servers, beds, and service rates based on patient flow and priority needs, striking a balance between reducing waiting times for critical cases and controlling operational costs. These mathematical models also account for practical constraints and stochastic variability inherent in clinical settings. Applications span emergency departments, outpatient clinics, and even pharmacy and blood service centers—showing significant improvements in system efficiency, reduced patient wait times, and enhanced overall care quality. Thus, mathematical programming is a powerful decision-support tool for queue management, offering evidence-based strategies to address congestion and resource allocation challenges in complex healthcare environments.

This study examines control activities in the delay in the return of Community Economic Empowerment (PEM) funds in Oeba Village, which is one of the policies of the Kupang City Government with interest-free funding assistance through the Community Empowerment Institution (LPM) of Oeba Village with the aim of developing productive businesses to increase the economic potential of the community. This study aims to determine the role of control activities in handling delays in the return of funds (PEM) and to determine the factors that cause the occurrence of arrears of funds (PEM) in Oeba Village, Kota Lama District. The type of data in this study is primary data obtained directly in the form of interviews with employees of the Community Empowerment Institution in Oeba Village. The data analysis technique used in this study is descriptive qualitative. The results of the study indicate that the delay in the return of funds (PEM) in Oeba Village is largely caused by weak supervision and performance reviews, in addition, inadequate human resource development and the absence of clear performance indicators hamper program evaluation. Factors causing PEM Fund arrears include business congestion, lack of understanding, minimal assistance to PEM fund recipients, poor financial management, and sanctions that are not strictly enforced

Traffic congestion in Jakarta has become a serious problem, affecting various aspects of life, such as time efficiency, environmental quality, and economic productivity. As one solution to overcome this problem, the Jakarta government is developing a mass public transportation system, including the Light Rail Transit (LRT). The LRT is expected to reduce congestion by providing a more efficient and environmentally friendly transportation alternative. In the process of planning and optimizing the LRT system, discrete mathematics, particularly graph theory, plays a very important role. Graph theory is used to model the LRT station network and track, with vertices representing stations and edges representing connecting lines between stations. With this model, various analyses can be performed to optimize the LRT line, such as finding the shortest path between two stations or evaluating the connectivity between existing stations. The use of graph theory allows the identification of more efficient routes, resulting in faster travel and reduced passenger waiting times. In addition, graph theory also plays a role in optimizing the LRT route by minimizing the number of transfers between stations or avoiding passenger congestion at certain stations. With proper route and network optimization, the LRT can make a significant contribution to reducing traffic congestion in Jakarta. Furthermore, the development of an efficient public transportation system also supports improved air quality and reduces reliance on private vehicles. Overall, the application of graph theory in LRT system planning is a strategic step towards creating more efficient and sustainable transportation in large cities like Jakarta. Beyond route optimization, graph theory is also very useful in analyzing route capacity and passenger distribution along the LRT system.

In recent years, rapid advancements in digital technology have significantly transformed global healthcare delivery. The COVID-19 pandemic acted as a catalyst, accelerating the integration of information technology into healthcare systems, particularly through the increased adoption of telemedicine. In the field of internal medicine, which often involves long-term care and management of chronic illnesses, telemedicine presents a promising solution to enhance service accessibility, improve care efficiency, and sustain favorable clinical outcomes. This study aims to conduct a narrative review to explore the impact of telemedicine on patient clinical outcomes, healthcare worker workload, and healthcare system efficiency within internal medicine practice. The review is based on an analysis of peer-reviewed literature published between 2020 and 2025, sourced from major databases including PubMed, Scopus, and Web of Science. Article selection was based on relevance to the topics of telemedicine and internal medicine, contextual applicability, and full-text availability. The findings of the review reveal that telemedicine contributes positively by expanding access to care, reducing travel time and logistical barriers for patients, accelerating clinical response times, and decreasing patient congestion in healthcare facilities. These outcomes are particularly beneficial for patients with chronic conditions who require regular monitoring and consistent communication with healthcare providers. However, the implementation of telemedicine also introduces new challenges, including increased administrative responsibilities and digital workload for healthcare professionals. The study underscores the importance of equipping healthcare systems with adequate digital infrastructure, implementing supportive and flexible policies, and providing comprehensive training for healthcare workers. These measures are crucial to ensure the successful and sustainable adoption of telemedicine in internal medicine. Overall, telemedicine holds strong potential to reshape the future of internal medicine, provided that its integration is strategically managed to balance technological advancement with human-centered care.