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All Journal Jurnal SOLMA INOVTEK POLBENG TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Applied Technology and Computing Science Journal Infotekmesin Indonesian Journal of electronics, electromedical engineering, and medical informatics Jurnal Elkolind : Jurnal Elektronika dan Otomasi Industri International Journal of Advances in Data and Information Systems Indonesian Journal of Engineering Research Educivilia: Jurnal Pengabdian Pada Masyarakat Elektriese: Jurnal Sains dan Teknologi Elektro Jurnal 7 Samudra Politeknik Pelayaran Surabaya Jurnal Cakrawala Maritim SISFOTENIKA Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Soft Computing Exploration
Dwi Sasmita Aji Pambudi
Department Of Marine Electrical Engineering, Shipbuilding Institute Of Polytechnic Surabaya
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The Experiment Practical Design of Marine Auxiliary Engine Monitoring and Control System Ruddianto, Ruddianto; Nugraha, Anggara Trisna; Pambudi, Dwi Sasmita Aji
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 4 (2021): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i3.212

Abstract

Maintaining the quality of transportation services and reducing operational costs are some of the problems in shipping companies. This problem can be solved by several solutions. One of them is a reliable machine alarm monitoring and operation system. This study aims to provide a practical design of the ship's auxiliary engine start-stop control system and alarm system. This study uses an experimental method with a descriptive explanation of the observations. The test results show that this system is able to provide a simple, inexpensive, and efficient engine alarm system design to develop this technology for shipping companies. The PLC used is suitable for controlling this system because of its fast response. In addition, the utilized HMI can communicate efficiently with the monitoring system showing the machine parameter interface directly. Direct application of the system has been created provides technology development solutions for monitoring and controlling systems auxiliary machines for shipping companies to reduce operational cost.
Design of Charger Controller on Wind Energy Power Plant with Arduino Uno Based on Pi Controller Nugraha, Anggara Trisna; Pambudi, Dwi Sasmita Aji; Utomo, Agung Prasetyo; Priyambodo, Dadang
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 4 (2021): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i3.214

Abstract

Technological developments are increasing every day. Most human activities do not escape the use of electrical energy. The increase in world fuel oil and its scarcity has led to many new innovations, one of which is the use of renewable energy. The most widely used renewable energy is solar, wind, and hydro energy. In order to support the effectiveness of the generator, a charger controller is needed to maintain battery performance. In this accumulator, the maximum voltage required to charge is 14.4 Volts. The problem that arises is how the voltage generated from the generator does not match the voltage required in the battery charging process. From this problem, a charger controller with a buck converter circuit with the PI method was made to stabilize the output voltage for charging. The aim o this study is to make a battery charger that can stabilize the level voltage of the battery charger. From the research, it was found that the efficiency value of the charger controller is 83-95%, and the average error percentage is 1.373%. For this reason, it can be concluded that the charge controller has good performance in terms of efficiency and percentage of output voltage error. The charger controller is expected to maintain battery performance and the lifetime of the battery
Spatio-Temporal AIS Big Data Analytics of Vessel Traffic Patterns in Kaohsiung Port Arfianto , Afif Zuhri; Santosa, Anisa Fitri; Sutrisno, Imam; Hasin, Muhammad Khoirul; Asmara, I Putu Sindhu; Riananda, Dimas Pristovani; Pambudi, Dwi Sasmita Aji
International Journal of Advances in Data and Information Systems Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v7i1.1504

Abstract

Maritime traffic management in major ports requires a comprehensive understanding of vessel movement patterns to ensure operational efficiency and safety. This study presents a spatio-temporal analysis of vessel traffic in Kaohsiung Port, Taiwan, utilizing a 10-month snapshot of AIS data (December 2024–October 2025). Employing quantitative methods including Kernel Density Estimation (KDE) for spatial intensity mapping, grid-based discretization for traffic density quantification, and temporal resolution analysis at multiple scales, the research identifies key operational hotspots and peak traffic periods. The analysis encompasses 1,247,890 AIS records from diverse vessel types, revealing distinct spatial clustering patterns in port entrance channels, anchorage zones, and terminal areas. Temporal analysis demonstrates pronounced diurnal and weekly cyclical patterns, with peak traffic intensities occurring during daytime operational hours and weekdays, reflecting commercial shipping schedules and port operational rhythms. The KDE-based hotspot identification reveals high-density zones concentrated within 0.5 nautical miles of major container terminals, indicating critical areas requiring enhanced traffic monitoring and collision avoidance measures. Grid-based traffic density quantification provides granular insights into vessel distribution across different port sectors, enabling zone-specific risk assessment and resource allocation strategies. The findings reveal complex spatio-temporal patterns that reflect the port's role as a major container hub in the Asia-Pacific region. Despite data quality limitations such as unspecified vessel types (59.9%) and incomplete destination fields, the results provide actionable insights for port authorities to enhance safety, optimize operations, and support strategic planning. This methodological framework demonstrates scalability and transferability to other port environments, contributing to the advancement of data-driven maritime traffic management systems
Automatic identification system big data‑driven maritime traffic density prediction in surabaya port using PCA and k‑means clustering Arfianto, Afif Zuhri; Haj, Muhammad Izzul; Muhammad Khoirul Hasin; Noorman Rinanto; Imam Sutrisno; Dimas Pristovani Riananda; Dwi Sasmita Aji Pambudi
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.v7i1.22

Abstract

The management of maritime traffic directly determines the level of operational efficiency and safety achievable at major ports, including Tanjung Perak in Surabaya, which serves as a critical logistics node for eastern Indonesia. This study presents a comprehensive analysis of maritime traffic density prediction using Automatic Identification System (AIS) big data combined with Principal Component Analysis (PCA) and K-Means clustering techniques. The dataset comprises 1,173 vessel movements recorded in December 2025, encompassing various vessel types, port operations, and voyage characteristics. Through dimensionality reduction using PCA and unsupervised clustering with K-Means, we identified 10 distinct traffic patterns representing different operational profiles. The analysis revealed significant temporal patterns, with peak traffic occurring at 14:00 (79 vessels) and lowest traffic at 02:00 (18 vessels). The clustering results achieved a silhouette score of 0.3863, effectively segmenting vessels based on voyage distance, capacity, speed, draught, and temporal features. The results of this research offer practical guidance for port authorities seeking to improve resource allocation, traffic management, and operational efficiency based on empirical evidence.
Co-Authors Abdullah, Kharis Adhitya, Ryan Yudha Agus Khumaidi Ahmad, Mahasin Maulana Ahmada, Ezra Adillafasyah Alfanda, Benedicta Dian Anggara Trisna Nugraha Anis Mustaghfirin Arfianto , Afif Zuhri Arfianto, Afif Zuhri Asmara, I Putu Sindhu Asri, Purwidi C. I. Sutrisno Cahyono, Luqman Dadang Priyambodo Dadang Priyambodo Didik Sukoco Dimas Pristovani Riananda Dimas Pritovani Riananda Dyah Arum Wulandari Ekki Kurniawan Eky Novianarenti Eky Novianarenti Emy Sofia Fortunaviaza Habib Ainudin Haj, Muhammad Izzul Hasin, Muhammad Khoirul Hendro Agus Widodo, Hendro Agus Hidayat, Mohammd Syafri Imam Sutrisno Imanuel, Petrus Chandra Lembang, Moses Yudha Dua Lilik Subiyanto M. Sarwoko M. Sarwoko Mayda Zita Aliem Tiwana Mayda Zita Aliem Tiwana Moh. Nur Khojim Muh. Anis Mustaghfirin Muh. Anis Mustaghfirin Muhammad Abid Al Fatih Muhammad Fikri Fathurrohman Muhammad Khoirul Hasin Nanda Dwi Pangestu Pramesti, Lely Primaningtyas, Widya Emilia Priyambodo Nur Ardi Nugroho Priyambodo Nur Ardi Nugroho Priyambodo, Dadang Purwoko, Ageng Rochmad Joko Putra, Zindhu Maulana Ahmad Raul, Raul Adam At Thariq Azhiim Ravi, Alwy Muhammad Riananda, Dimas Pristovani Rinanto, Noorman Ruddianto Ruddianto Ruddianto, Ruddianto Ryan Yudha Adhitya Santosa, Anisa Fitri Setiyoko, Annas Singgih Sugeng Santoso Sumardiono Sumardiono, Sumardiono Utomo, Agung Prasetyo Wulandari, Kiki Dwi Yuniati, R.A. Norromadani Yuning Widiarti Zhafirah, Talitha Amalia Zindhu Maulana Ahmad Putra