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All Journal Jurnal Teknologi Sistem Informasi dan Aplikasi Meteor STIP Marunda International Journal Of Science, Technology & Management (IJSTM) Maritime Park: Journal Of Maritime Technology and Socienty Journal of Soft Computing Exploration
Prakosa, Dandun
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Analysis of Traffic Performance and Handling Scenarios in the Malang Station Area, Kota Baru Prakosa, Dandun; Jamhari, Syafek; Veronica, Veronica; Irfan Efendi, Ade
International Journal of Science, Technology & Management Vol. 7 No. 1 (2026): January 2026
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v7i1.1404

Abstract

The Malang Kota Baru Station area is currently experiencing traffic performance problems characterized by high delays and low speeds, especially on the Trunojoyo 1 Road and Trunojoyo 2 Road sections. This condition is influenced by high side obstacles in the form of on-street parking and loading and unloading activities. This study aims to analyze the performance of the existing road network and formulate effective traffic management and engineering scenarios in improving regional traffic performance. The analysis was carried out by modeling using PTV Vissim software through the calibration and validation stages using the Geoffrey E. Havers (GEH) statistical test. The results of the analysis of existing conditions showed an average delay of 168 seconds, network speed of 13.6 km/h, total mileage of 24,120 kend-km, and total travel time of 1,774 vehicles/hour, which indicates that the performance of the road network is in the poor category. Improvement efforts are carried out through several traffic management and engineering scenarios, including moving on-street parking to off-street, repairing pedestrian facilities, adding signs and repairing road markings, as well as regulating the separation of access in and out of goods and passengers. The results of the proposed scenario simulation showed an improvement in road network performance, namely an increase in network speed to 22.04 km/h, a decrease in average delay to 90.91 seconds, a decrease in total travel time to 1,160.59 vehicles/hour, and an increase in total mileage to 25,574 kend-km. Thus, the proposed traffic management and engineering scenario has proven to be effective in improving traffic performance in the Malang Kota Baru Station Area.
Determination of the Shortest Route with the Djikstra Algortima in the Operation of Aplousing and Maintenance of Shipping Navigation Aids (SBNP) Wanadi, M Adil Wanadi; Kusuma, Wisnu Wardana; Efendi, Ade Irfan; Rizal, Yus; Prakosa, Dandun
Maritime Park: Journal of Maritime Technology and Society Volume 5, Issue 1, 2026
Publisher : Department of Ocean Engineering, Faculty of Engineering, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62012/mp.vi.46426

Abstract

This study aims to implement the djikstra algorithm to overcome the problem of optimizing the shortest route determination in aplousing and maintenance activities of Shipping Navigation Assistance Facilities (SBNP) in the working area of the Tanjung Perak Type A Navigation District Office. The Navigation Pier has historically been a strategic facility to face the challenges of maintaining fuel efficiency, sailing times and reducing emissions in environmental pollution due to suboptimal routes. The djikstra algorithm is known to be effective in finding the shortest route on a weighted graph by representing strategic location points such as ports and marine navigation areas as nodes and the distance between nodes is calculated using the haversine formula based on geographic coordinates as weights. Before the implementation of travel route optimization, a total mileage of 1,210.30 km was obtained and after the optimization was applied using the djikstra algorithm, a total mileage of 1,110.44 km was obtained. This comparison shows a significant distance savings of 99.86 km or 8.25% travel efficiency. This optimization is able to contribute to time reduction, fuel savings and reduction of environmental pollution exhaust gas emissions so that it is able to optimize the operational effectiveness of ships as a whole. This study confirms the positive and relevant capabilities to be applied in shipping navigation route planning and support decision-making in the management of sea routes or logistics transportation in areas with a varied distribution of mileage points that require high efficiency and mobility. In the next research, it is hoped that it will be able to add external factors such as sea currents, waves, and wind according to the geographical characteristics of the territorial waters so that the results of route planning can be more accurate in the real operational area in the shipping work area.
Implementasi Algoritma Traveling Salesman Problem (TSP) dalam Penentuan Jalur Terpendek pada Rute Berlayar untuk Kegiatan Aplousing dan Perawatan SBNP di Wilayah Kerja Kantor Distrik Navigasi Tipe A Tanjung Perak Adil Wanadi, M.; Irfan Efendi, Ade Irfan Efendi; Prakosa, Dandun; Rizal, Yus
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 9 No. 1 (2026): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v9i1.59095

Abstract

The aplousing and maintenance activities of Shipping Navigation Assistance Facilities (SBNP) in the work area of the Tanjung Perak Type A Navigation District provide high efficiency in fuel use and travel time while minimizing the impact of environmental pollution. However, the shipping route so far has not been optimal, resulting in longer mileage, requiring excess fuel consumption and increased exhaust emissions. This study aims to optimize shipping routes through the application of the Traveling Salesman Problem (TSP) algorithm. The two approaches used are Heuristic Nearest Neighbor and Brute Force with case studies on 11 port points and islands in the waters of East Java. The simulation results showed that the Brute Force approach produced the most optimal route with a total distance of ±1,095.94 km more efficient than the Nearest Neighbor ±1,110.33 km and the initial route without optimization of ±1,284.3 km. This reduction in mileage has a positive impact on fuel savings, shipping time and reducing exhaust emissions. This study proves that the application of the TSP algorithm is able to increase operational efficiency and has the potential to be the basis for the development of technology-based decision-making support systems in environmentally friendly shipping route management.
Effectiveness Analysis of Indonesia's Port State Control Inspection Under Tokyo MOU: A Mixed-Methods Approach Schouten, Femmy Sofie; Wanadi, M. Adil; Kusuma, Wisnu Wardana; Pramono, Agus; Prakosa, Dandun; Laksamana, Rio
Meteor STIP Marunda Vol 18 No 1 (2025): June
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat (P3M) STIP Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36101/msm.v18i1.415

Abstract

Port State Control (PSC) represents a critical mechanism for ensuring maritime safety, environmental protection, and compliance with international shipping regulations. As a member of the Tokyo Memorandum of Understanding (Tokyo MOU), Indonesia conducts PSC inspections to monitor foreign vessels operating within its territorial waters. This study examines the effectiveness of Indonesia's PSC inspections under the Tokyo MOU framework through comprehensive analysis of ship detention trends, common deficiencies, and regulatory enforcement challenges. A mixed-methods research approach is employed, combining quantitative analysis of PSC inspection and detention data from 2018-2022 with qualitative assessments of inspection procedures and regulatory frameworks. Findings indicate that while Indonesia has demonstrated improvement in PSC implementation, significant challenges persist in inspection consistency, resource allocation, and systematic coverage. The study reveals that Indonesia conducts an average of 1,542 annual inspections with a detention rate of 5.2%, yet inspection coverage remains at 35-40% of total foreign vessel arrivals, below the regional average of 70%. The research highlights the critical need for enhanced coordination among maritime authorities, comprehensive inspector training programs, and stricter regulatory compliance mechanisms to optimize inspection effectiveness. The study concludes that implementing a more rigorous and consistent PSC approach will contribute significantly to safer maritime operations and reduced environmental risks. This research contributes to maritime safety literature by providing empirical insights into PSC implementation challenges in developing maritime nations, accompanied by evidence-based policy recommendations to strengthen regulatory practices and advance global maritime safety standards.
Predicting willingness to pay for urban rail transit using machine learning : Evidence from jakarta MRT Kusuma, Wisnu Wardana; EFENDI, ADE IRFAN EFENDI; Prakosa, Dandun; Montanasyah, M. Popik Montanasyah; wanadi, adil; Rizal, Yus
Journal of Soft Computing Exploration Vol. 7 No. 1 (2026): March 2026
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v7i1.18

Abstract

The development of urban transportation requires an efficient, reliable and sustainable system, so fare determination is an important factor in the success of the Jakarta MRT service. In this context, understanding the user's Willingness to Pay (WTP) is crucial because it is not only influenced by economic ability, but also perception and preference for services. This study aims to analyze and predict the WTP of MRT users by integrating transportation economics approaches and machine learning methods. The research data is in the form of primary data from a survey of 296 MRT users which includes socio-economic characteristics, transportation costs, frequency of use and Ability to Pay (ATP). The methodology used includes descriptive analysis and regression modeling using various algorithms, namely Linear Regression, Decision Tree, Random Forest, Gradient Boosting, Support Vector Regression (SVR) and XGBoost. Model evaluation was carried out using MAE, RMSE and determination coefficient (R²). The results showed that the value of WTP was relatively homogeneous compared to variations in income and transportation costs, which indicated that willingness to pay was not entirely determined by economic ability. The performance of the model shows that no algorithm is consistently superior, with R² values that tend to be low. The feature importance analysis identified income, transportation costs and ATP as the main factors. This research contributes through the application of a multi-model machine learning framework and policy implications that MRT fare determination needs to consider economic aspects and user preferences in a balanced manner.
Co-Authors Adil Wanadi, M. Agus Pramono Efendi, Ade Irfan Efendi, Ade Irfan Efendi Femmy Schouten Irfan Efendi, Ade Irfan Efendi, Ade Irfan Efendi Jamhari, Syafek Laksamana, Rio M. Adil Wanadi Montanasyah, M. Popik Montanasyah rizal, Yus VERONICA VERONICA Wanadi, M Adil Wanadi Wanadi, M. Adil Wisnu Wardana Kusuma