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International Journal of Marine Engineering Innovation and Research
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 25415972     EISSN : 25481479     DOI : ttp://dx.doi.org/10.12962/j25481479
Core Subject : Science, Social, Engineering,
Automotive Engineering Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Transportation
International Journal of Marine Engineering Innovation and Research (IJMEIR) is an open-access journal, which means that visitors all over the world could publish, read, download, cite and distribute papers published in this journal for free of cost. IJMEIR journal has a vast group of visitors, a far-reaching impact and pretty high citation. IJMEIR adopts a peer-review model, which insured fast publishing and convenient submission. IJMEIR now cordially inviting you to contribute or recommend quality papers to us. This journal is geared towards the dissemination of original innovation, research and practical contributions by both scientists and engineers, from both academia and industry. Theses, dissertations, research papers, and reviews associated with all aspects of marine engineering, marine sciences, and marine technology are all acceptable for publication. International Journal of Marine Engineering Innovation and Research (IJMEIR) focus and scopes are preserve prompt publication of manuscripts that meet the broad-spectrum criteria of scientific excellence. Areas of interest include, but are not limited to: Automotive Biochemical Biology Biomedical science Biophysics and biochemistry Chemical Chemistry Combat Engineering Communication Computer science Construction Energy Energy storage Engineering geology Enterprise Entertainment Environmental Environmental Engineering Science Environmental Risk Assessment Environmental technology Financial Engineering Fire Protection Engineering Fisheries science Fishing Food Science and Technology Health Care & Public Health, Health Safety Health Technologies Industrial Technology Industry Business Informatics Machinery Manufacturing Marine Engineering Marine sciences Marine technology Marine biology Marine economic Marine engines Marine fisheries Marine fuel Marine geology Marine geophysic Marine management Marine oil and gas Marine policy Material sciences Materials science and engineering Mathematics Mechanics Medical Technology Metallurgical Micro-technology Military Ammunition Military Technology Military Technology and equipment Mining Motor Vehicles Naval Engineering Neuroscience Nuclear technology Ocean Robotics and Automation Safety Engineering Sanitary Engineering Space Technology Statistics Traffic Transport Visual Technology
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Articles 31 Documents
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Search results for , issue "Vol. 10 No. 1 (2025)" : 31 Documents clear
The Effect of Coconut Fiber Usage and Clamshell Powder Replacement for Calcium Silicate Board’s Bending Strength Khafifulloh Al Faqih Zam Zammi; Widya Emilia Primaningtyas; Imah Luluk Kusminah; Novi Indah Riani; Rahma Rei Sakura; Benedicta Dian Alfanda
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4744

Abstract

Calcium silicate boards (CSB) are being explored in the maritime industry due to the mechanical strength and its resintance to humidity. The common CSB comprises fiber, silica sand, and portland cement. Clamshell is one of marine waste, who has a high calcium carbonate (CaCO3) content. Coconut fiber, a natural fiber known for its high strength and durability, presents sustainable solutions for enhancing the material properties of CSB. This study explores the forming mechanism and mechanical properties of the CSB in the usage and varied volume fraction addition of coconut fiber with the varied portion replacement silica sand using clamshell powder. The bending test was performed, and the experimental results were analyzed using ANOVA, to understand the effect of the mixture composition on the bending strength of the CSB. The addition of volume fraction coconut fiber significantly improve the bending strength of the boards, while the replacement of silica sand using clamshell powder gives various result. The maximum bending strength was 13.87 ± 0.64 Mpa by 0% clamshell powder replacement in 9% coconut fiber, and significantly drop at 8.26 ± 2.20 MPa by 50% clamshell powder with 50% silica sand. In fully portion replacement of silica sand, in which the addition of 100% clamshell powder, with 9% coconut fiber, the bending strength measured at 10.29 ± 1.31 MPa. The highest results exceeding the minimum requirement in ISO-8336 category A and B (saturated condition) , class 3 (>13 MPa) standards for interior wall installations. This study providing a more robust and eco-friendly materials alternatives that supports non or maritime industry needs in while resolve the environmental issue.
Alternative Neutralizers for Acid Mine Wastewater: Characterization and Neutralizing Potency of Pond Ash and Concrete Sludge Dion Awfa; Rifka Noor Azizah; Ahmad Daudsyah Imami; Resarizki Utami; Edo Kharima Army; Evi Eri Narita; Muhammad Meiko Cahya Anugrah; Nasrul Putra; Wisnu Prayogo; Novriadi
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4745

Abstract

One of the most widely used fuels is coal, where the South Sumatra region is an area with coal potential whose production is still being increased. On the other hand, there are negative impacts caused by coal exploration activities, one of which is mining runoff, commonly called acid mine drainage. Acid mine drainage has a low pH and contains inorganic constituents such as iron and manganese. Therefore, proper and optimum information processing is needed to support environmentally friendly mining management. In contrast, alternative materials such as blast furnace slag, wood ash, fly ash, cement kiln dust, and construction waste are being used. These materials are effective against AMD, at a relatively low cost, and outperform traditional neutralizers. However, comparing them with conventional agents is challenging due to limited data and experimental variation. In this study, the objectives to be achieved are 1) to determine the quality conditions of AMW at the study location, 2) to determine the effectiveness of the use of chemical and alternative compound neutralization agents in the processing process, and 3) to provide recommendations for the dosage, type of neutralization agent, and the most optimum time in AMW processing. The AMW obtained is then subjected to laboratory analysis related to quality, including TSS, pH, Fe, and Mn parameters. In addition, conventional and alternative neutralization agents are also prepared and then used to process AMW. Then, experiments were carried out on variations in the type of neutralization agent, the dosage of neutralization agent use, and the contact time between the neutralization agent and AMW. Experimental results have shown that these materials, mainly pond ash and concrete sludge, can effectively neutralize pH and reduce Mn concentrations by up to 83.26% and 79.12%, respectively. Similarly, Fe concentrations can be reduced by up to 80.76% and 74.05% using pond ash and concrete sludge, respectively. While these results are promising, future research should focus on characterizing the generated sludge to confirm the adsorption of ferrous and manganese ions onto the surface of the alternative neutralizers.
Phenetic Diversity and Relationships of Sea Lettuce (Ulva spp.) on the Southern Coast of Gunungkidul Yogyakarta Indonesia Abdul Razaq Chasani; Melinda Windiana Febrianti; Muhammad Said Rifqi
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4746

Abstract

The development of tourism areas in the Gunungkidul coastal zone was a potential threat that can affect the marine macroalgae diversity. In order to prevent the decline of macroalgae diversity from these anthropological threats, a comprehensive study is needed to record the population dynamics that occur. The objective of this study is revealing the species diversity and phenetic relationship of the sea lettuce (Ulva spp.). Phenetic analysis of sea lettuce was conducted by observing morphological, anatomical, and biochemical characters. Clustering analysis was done by the UPGMA method, whereas ordination analysis was conducted using the PCA (Principal Component Analysis) method; both of them were calculated using the MVSP 3.1 program. The result of the study discovered four species of Ulva, i.e., Ulva lactuca, Ulva rigida, Ulva compressa, and Ulva linza. The reconstruction of phenetic relationships revealed two main clusters of sea lettuce, exhibiting a percentage difference of 75.2. The PCA analysis exhibited eight characters that significantly influence clustering patterns, including thallus color, blade width, blade thickness, blade hole, stiff edge cells, cell surface diameter, elongated cell shape, and the presence of violaxanthin and neoxanthin.
Enhancing Oil Spill Detection and Response: An Overview of Satellite-based Observation Technologies and Their Impact Muhammad Iqbal Habibie; Robby Arifandri; Zulfa Qonita; Pronika Kricella; Muhammad Hisyam Khoirudin
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4747

Abstract

Oil spills are a major environmental issue that requires prompt detection and effective response strategies. Remote sensing technologies have shown great potential in improving oil spill detection and management. This paper aims to review and compare various remote sensing techniques and models used for oil spill detection and response, with a focus on evaluating their effectiveness in preventing offshore oil spills. The study involves a comprehensive review of recent research on remote sensing methods, such as neural network-based detection, Synthetic Aperture Radar (SAR), and optical sensors, alongside oil spill response techniques. The paper also utilizes the Publish or Perish (PoP) tool to analyze scientific papers related to oil spill detection and response. The PoP tool was employed to examine citation metrics, methodologies, and trends from 187 studies, including 16 focused on remote sensing techniques, 21 on oil spill methods, and 47 on related concerns. Results indicate that neural network-based methods are effective in high-risk areas, while SAR-based detection is recommended for regions with high sea states or cloud cover. The study also finds that a combination of response techniques, such as containment booms and bioremediation, can significantly improve the effectiveness of oil spill management. Moreover, the integration of multi-sensor data and machine learning techniques shows promise in enhancing detection accuracy and reducing false positives. In conclusion, the paper highlights the need for improved sensor technologies and the integration of various detection and response methods to enhance oil spill management efforts. Future research should focus on refining these techniques and developing cost-effective solutions to enable more efficient and timely responses to oil spills.
Critical Chain Project Management and Buffer Planning: Study Case at Security Accommodation Vessel Construction Bella Puji Darma Samodra; Agoes Santoso; Ede Mehta Wardhana
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4748

Abstract

Shipbuilding projects frequently encounter delays and cost overruns as a result of unpredictability in the construction process. This paper aims to explore the potential of Critical Chain Project Management (CCPM) and buffer planning to enhance scheduling in complex shipbuilding project. The research approach involves a case study of a Security Accommodation Vessel (SAV) construction project, complemented by expert interviews which were conducted to assess the risks and uncertainties affecting activity durations. The buffer sizes were then calculated using the Root Square Error Method (RSEM). Qualitative data was gathered through interviews with the expert to identify and assess potential risks and uncertainties impacting activity durations. This qualitative insight informed the application of the RSEM to determine appropriate buffer sizes. The planned project duration was reduced from 790 days to 678 days, representing a 14,5% improvement. The study focuses on the planning phase of CCPM and demonstrates the potential of combining CCPM, buffer planning, and expert input to create more reliable schedules for complex shipbuilding projects like SAV construction.
Optimizing Laundry Wastewater Treatment: A Hybrid Approach Using Poly-Aluminum Chloride Coagulation and Activated Carbon Adsorption Sugito; Aliffia Rica Ambima; Muhammad Al Kholif; Firda Lutfiatul Fitria
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4753

Abstract

Laundry wastewater contains high levels of Chemical Oxygen Demand (COD) and phosphate (PO4), contributing to water pollution and eutrophication. This study investigates an integrated treatment approach using poly-aluminum chloride (PAC) coagulation and activated carbon adsorption to improve wastewater treatment efficiency. The research aims to determine the optimal PAC dosage (10% and 15%) and stirring time (0, 5, 15, 30, and 45 minutes) for maximizing COD and PO4 removal. A batch reactor system was used to conduct the treatment process, and the analysis followed the Indonesian National Standard (SNI) methods. The results demonstrated that the highest removal efficiencies were achieved with a 15% PAC dosage and a stirring time of 45 minutes. Under these conditions, COD levels were reduced from 2189.62 mg/L to 143.47 mg/L, achieving a 93% reduction. Similarly, PO4 levels decreased from 94.33 mg/L to 5.18 mg/L, corresponding to a 96% removal rate. These findings indicate that the combination of PAC coagulation and activated carbon adsorption is a highly effective treatment method for reducing pollution in laundry wastewater. This hybrid approach meets environmental discharge standards and presents a sustainable solution for large-scale wastewater treatment applications.
Artificial Intelligence in Integrated Marine Observing Systems: A Comprehensive Review Soni Adiyono; Muhammad Arifin; Noor Latifah; Eko Darmanto
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4754

Abstract

The marine ecosystem is vital for sustaining life on Earth, yet its vastness and complexity present significant challenges for effective monitoring and management. Integrated Marine Observing Systems (IMOS) have emerged as essential tools for understanding and protecting marine environments. This study aims to systematically review the integration of artificial intelligence (AI) into IMOS, focusing on its contributions to data processing, biodiversity monitoring, and environmental change analysis. A systematic literature review (SLR) method is employed to analyze existing research and identify key AI techniques and their applications in marine and oceanographic studies. Results indicate that deep learning is the most widely used AI method, with marine research being the primary application domain. Other areas, such as environmental monitoring and industrial systems, also demonstrate considerable potential. However, data inconsistency, operational limitations, and the lack of standardized frameworks remain significant barriers. This review highlights the transformative role of AI in enhancing IMOS capabilities and provides recommendations for addressing existing challenges to support sustainable marine management.
Blue Economy: Framework for Integrating Economic Growth with Marine Ecosystem Ram Priye Kumar Sahu; Raviteja Doppalapudi
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4758

Abstract

The Blue Economy is an economic framework that integrates economic growth with marine ecosystem sustainability, acknowledging the oceans as vital to global development. The concept gained prominence at the Rio+20 United Nations Conference on Sustainable Development in 2012, emphasizing the need for a sustainable ocean-based economy that balances economic opportunities with environmental conservation and social equity. It encompasses a wide range of sectors, including fisheries, aquaculture, maritime transport, marine biotechnology, renewable energy, and coastal tourism, all of which play a crucial role in global trade, food security, and employment generation. The objective of this paper is to examine the evolution, components, opportunities, and challenges of the Blue Economy while identifying pathways for its sustainable development. The study follows a qualitative approach by analysing existing literature, global policy frameworks, and case studies to evaluate the effectiveness of different ocean-based economic models. Findings indicate that while the Blue Economy presents immense potential for economic growth and employment, it faces several critical challenges, such as overfishing, habitat destruction, climate change impacts, and governance issues. The exploitation of non-living marine resources, such as deep-sea mining and offshore oil and gas extraction, also raises concerns about long-term ecological sustainability. To overcome these challenges, the paper highlights the importance of strong governance frameworks, investment in marine research and technology, and the development of policies that promote sustainable resource management. The role of marine protected areas, sustainable fishing practices, and advancements in renewable ocean energy is emphasized as key strategies for balancing economic benefits with environmental conservation. The private sector, in collaboration with governments and international organizations, must play a central role in driving sustainable investments and innovations. Ultimately, the Blue Economy has the potential to support long-term economic development while preserving marine biodiversity and improving the livelihoods of coastal communities. By adopting sustainable practices, enforcing regulations, and investing in science and data-driven decision-making, nations can harness ocean resources responsibly. This paper underscores the need for an integrated approach that aligns economic growth with environmental stewardship, ensuring that the benefits of ocean-based industries are equitably shared while safeguarding marine ecosystems for future generations.
Deep Learning for Tidal Flood Prediction in West Pandeglang Waters, Banten Nevin Adel Ramaputra; Asep Sandra Budiman; Willdan Aprizal Arifin
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4759

Abstract

Tidal flooding poses a significant threat to coastal areas, exacerbated by rising sea levels. In West Pandeglang Waters, Banten, frequent tidal floods impact communities, necessitating accurate prediction models for effective disaster mitigation. This study aims to develop a deep learning-based tidal flood prediction model using Keras and TensorFlow. The model incorporates oceanic and atmospheric variables, including sea surface height, wave characteristics, wind components, and precipitation data from 2003 to 2023. To address data imbalance, Synthetic Minority Over-sampling Technique (SMOTE) and MinMax scaling were applied, ensuring balanced class distribution. The model was trained and evaluated using a dataset comprising 11,808 samples, achieving an accuracy of 86% and an area under the curve (AUC) of 0.93. These results indicate a strong capability to differentiate between flood and non-flood conditions. The study demonstrates the effectiveness of deep learning in predicting tidal floods, providing valuable insights for early warning systems and coastal management in flood-prone regions.
Effectiveness of Mechanical and Chemical Filter Application on Water Quality, Phytoplankton, and The Emergence of Vibrio Bacteria in Intensive Shrimp Pond Indra Febriantoro; Mohammad Fadjar; Maftuch
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4760

Abstract

The aquaculture sector plays a crucial role in Indonesia's fisheries industry, especially with the rapid growth of Litopenaeus vannamei shrimp farming. However, intensive aquaculture systems face significant challenges, such as decreased water quality and increased Vibrio bacterial infections, which have the potential to cause diseases with high mortality rates. This study aimed to evaluate the effectiveness of mechanical and chemical filtration systems in improving pond water quality, maintaining phytoplankton balance, and suppressing pathogenic bacterial populations. This study was conducted for 30 days using a randomized group design (RAK) with three treatments, namely ponds without filtration (K), ponds with mechanical filtration (FF), and ponds with chemical filtration (FK). The results showed that chemical filtration was more effective in reducing total organic matter (TOM) and reducing Vibrio density to 1,740-1,880 CFU/mL. Meanwhile, mechanical filtration was more optimal in increasing the phytoplankton population to reach 123,000 ind/m³. The application of the filtration system was also shown to increase dissolved oxygen (DO) levels and reduce total suspended solids (TSS), thus creating more stable water conditions for shrimp. The results of this study indicate that the implementation of an appropriate filtration system can be a strategic solution in supporting the sustainability of the L. vannamei aquaculture industry in Indonesia.

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