Traffic congestion in commercial areas is a chronic problem that not only hampers the efficiency of urban mobility but also has economic, social and environmental impacts. Various cities in Indonesia have implemented traffic management approaches, such as traffic engineering, traffic light timing, and motor vehicle restrictions, but the effectiveness of implementation at the local level is often not systematically documented. The rapid growth in the number of private and public transport vehicles traveling on these main roads, while limited road capacity, exacerbates the congestion situation (Sarwandy et al., 2024; Widodo et al., 2024). In this context, research focusing on micro-level commercial areas such as Jl. Karanggetas in Cirebon City plays an important role in filling the literature gap and providing an empirical foundation that can be applied directly by policy makers.

Based on the Indonesian Road Capacity Guidelines (PKJI) 2023, an analysis of road conditions and congestion in this area shows that the main roads in this commercial area often experience saturation. Vehicle volumes exceeding road capacity, coupled with illegal parking and irregular loading and unloading activities, are the main factors causing congestion in this area (Alyani et al., 2025; Budiati et al., 2024). Ineffective traffic management in such areas, given the mismatch between road infrastructure and the number of vehicles, requires a more adaptive and locally context-based managerial approach.

This study is novel in three main aspects. First, it highlights secondary commercial areas in mid-tier cities that often escape macro-planning attention despite their central role in supporting urban economic activity. Jl. Karanggetas, as a commercial hub with mixed vehicle flows (city transport, private vehicles, and goods vehicles), provides a representative case study of traffic management challenges in the context of mid-sized urbanization. Most of the previous literature has focused on metropolitan cities such as Jakarta and Surabaya, while Cirebon with its rapid economic growth but inadequate infrastructure offers different dynamics and requires an adaptive management approach. Therefore, this study focuses on analyzing traffic congestion on Jl. Karanggetas, Cirebon City, to provide solutions that are more relevant and contextual to local conditions (Samal et al., 2022; Yamanari et al., 2022).Second, the approach used in this study combines spatial mapping, analysis of congestion time patterns, as well as the involvement of local stakeholders (road users, traders, and the Transportation Agency). This enabled a comprehensive understanding of the sources of congestion, including the contribution of illegal parking, peak hour goods distribution, and the imbalance between road capacity and vehicle volume. This interdisciplinary approach has not been widely adopted in similar studies that predominantly use quantitative approaches.

Third, this study offers a prototype of traffic management based on local needs and road user behavior. In most transportation policies, generic top-down solutions often fail to capture local complexities. This study, based on direct observation and field data on Jl. Karanggetas, produces more contextualized technical and policy recommendations, such as repositioning parking zones, providing dedicated lanes for goods vehicles, and regulating off-peak loading

and unloading times. These local data-based policy adjustments are a real contribution in streamlining the implementation of traffic management.

As urbanization is expected to reach 68.4% by 2050 (Yamanari et al., 2022), challenges related to traffic congestion in commercial areas are increasingly urgent. Therefore, this research is very relevant in formulating traffic management policies that can be adapted quickly to changing conditions and economic growth in medium urban areas such as Cirebon City.

To analyze overall road performance, road geometrics need to be evaluated using PKJI 2023 standards, then combined with Level of Service (LOS) to identify traffic flow conditions, along with side obstacle analysis based on the results of the questionnaire distribution.

Congestion

Based on the correlation table analysis, the relationship between variables in this study shows a relatively low association. There is a weak positive correlation (0.23) between compliance with traffic rules and frequency of congestion on Jl. Karanggetas, indicating that road user compliance only slightly affects congestion, possibly due to external factors such as limited road capacity. In contrast, the frequency of congestion has a negative relationship (-0.31) with the impact on productivity, meaning that the more often one is stuck in traffic, the greater the perceived decrease in productivity. This finding suggests that technical solutions, such as improving road geometrics or adding lanes, are more important than simply socializing traffic rules.

Based on the results of the traffic analysis on Jl. Karanggetas, peak congestion occurs at 11:00-14:00 with the classification of side obstacles in the "very high" category. The level of service (LoS) at that time is in the B and C categories, indicating that traffic flow is starting to be disrupted and less stable due to insufficient road capacity. This finding is in line with Hanson & Giuliano's (2021) urban transportation system theory, which states that the imbalance between demand and supply of road capacity is the main cause of congestion in urban areas.

The correlation test results show weak relationships between road user perception variables, including between traffic compliance and frequency of congestion (r = 0.233) and a moderate negative relationship between frequency of congestion and reduced productivity (r = -0.314). This suggests that technical solutions are more influential than educational efforts alone, as confirmed by Litman (2022) and Purwanto et al. (2023). Traffic management recommendations such as the structuring of parking zones, logistics timing, and the construction of angkot shelters are all the more relevant because they directly address the problems observed on the ground. Dedicated angkot stops, for example, are important to prevent the practice of loading and unloading passengers at random points, which has been one of the main causes of congestion.

A local needs-based approach and the integration of monitoring technology (e.g. CCTV and traffic monitoring applications), as recommended in the Artificial Intelligence-Based Real-Time Traffic Management study (2023), is considered effective in strengthening traffic management strategies in mid-level commercial areas such as Jl. Karanggetas.

Congestion in the commercial area of Jl. Karanggetas, Cirebon City, occurs due to a combination of limited road capacity and road user behavior. Problems such as illegal parking, loading and unloading activities during peak hours, as well as lack of supervision and supporting infrastructure such as official parking zones, cause disrupted and unstable traffic flow. The analysis also shows that the correlation between road users' perception of traffic compliance and congestion is relatively weak, signaling the need for solutions that are more technical and structural than merely educational. Strategic recommendations from this study include the elimination of on-street parking, repositioning parking zones, limiting the time of logistics activities, implementing monitoring technology (CCTV and application-based traffic information systems), and building angkot stops at strategic points. These stops are expected to reduce the practice of raising or lowering passengers carelessly, which often causes traffic obstacles. This approach is contextual, and responsive to the actual needs of the area. The phased implementation of this solution can also serve as a model for handling congestion in similar commercial areas in other developing cities.

Traffic management in commercial areas is increasingly important in the face of congestion due to population growth and technological advances. The surge in population in urban areas leads to an increase in vehicle volume, which has a negative impact on mobility, economic activity, and environmental quality. To address these issues, the application of advanced technologies such as real- time traffic information systems, navigation applications, and big data analysis can provide up-to-date information and help plan more effective transportation policies. Adaptive policies, such as regulating heavy vehicle operating hours and developing efficient public transportation, are also needed to reduce traffic congestion. With the right integration of technology and policy, traffic management can be more responsive to the dynamics of population growth, creating a more comfortable and productive environment.

We would like to thank all those who have contributed to this research. We greatly appreciate the support and guidance from our parents and supervisors who have provided valuable guidance. Thank you also to our friends who have provided support and input during this research process. We appreciate the participation of respondents who have taken the time to contribute to data collection. In addition, we are grateful to the institutions and organizations that have provided the necessary resources and facilities. We hope that the results of this study can provide benefits and positive contributions to the development of science and society.